{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import torch.nn as nn\n",
    "import torch\n",
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "torch.set_default_tensor_type(torch.DoubleTensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#绘制序列\n",
    "def plot_series(time,series,format=\"-\",start=0,end=None,label=None):\n",
    "    #根据时间轴和对应数据列表绘制序列图像\n",
    "    plt.plot(time[start:end],series[start:end],format,label=label)\n",
    "    #设置横纵轴意义\n",
    "    plt.xlabel(\"Time\")\n",
    "    plt.ylabel(\"Value\")\n",
    "    #设置图例说明字体大小\n",
    "    if label:\n",
    "        plt.legend(fontsize=14)\n",
    "    #显示网络\n",
    "    plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#趋势模式\n",
    "def trend(time,slope=0):\n",
    "    #序列与时间呈线性关系\n",
    "    return slope*time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#白噪声\n",
    "def white_noise(time,noise_level=1,seed=None):\n",
    "    #生成正态分布的伪随机数序列\n",
    "    rnd=np.random.RandomState(seed)\n",
    "    #noise_level控制噪声幅值大小\n",
    "    return rnd.randn(len(time))*noise_level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#季节性（周期性）模式\n",
    "def seasonal_pattern(season_time):\n",
    "    \"\"\"Just an arbitrary pattern,you can change it if you wish\"\"\"\n",
    "    #分段函数（自变量取值[0，1]作为一个模式\n",
    "    return np.where(season_time<0.4,\n",
    "                   np.cos(season_time*2*np.pi),\n",
    "                   1/np.exp(3*season_time))\n",
    "\n",
    "#将某个季节性（周期性）模式循环多次\n",
    "def seasonality(time,period,amplitude=1,phase=0):\n",
    "    \"\"\"Repeats the same pattern at each period\"\"\"\n",
    "    #将时间映射到0-1之间\n",
    "    season_time=((time+phase)%period)/period\n",
    "    return amplitude*seasonal_pattern(season_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#时间\n",
    "time=np.arange(4*365+1)\n",
    "#只包含上升趋势的序列\n",
    "series=trend(time,0.1)\n",
    "#设置画布大小\n",
    "plt.figure(figsize=(10,6))\n",
    "#根据time series绘制序列\n",
    "plot_series(time,series)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#设置季节性幅值\n",
    "amplitude=40\n",
    "#生成季节性序列\n",
    "series=seasonality(time,period=365,amplitude=amplitude)\n",
    "#绘制序列\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(time,series)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EwSvrdL/J0iKsAG4JWIVNzM0krrRv3dSaiUbzbEIUkyBZElH3k9gnaynq2PL67Bj7wVYkXQCiY5AfxMmUqSQnl/mOD2VFsd6RgmjW1njn9QFIgy9KEsTx3EFTFCdJmYJkVlKoit3WzlEd8xfM0oByACdiXHwQFbFrzFIgmRUmGmpJN+2TCi9IY0Y4+NeKvTh4ynvrC5EoOmzaLRNhP7rW7X41ZuL9fhh59wx8P+RuC3ZMTXUpf5WRE+eHIGiz44qPlFdJ0/buuEIyaytCAFx7lpO+9SImfevFyARlIAZTZieIY1bqQpcJJJiVKCt2HcfIu2coV6eYcqyhBY0t2SXhJxpb8bkn3wgV7ytUv01Bp9chK96yHcfw5JKdvu73K5ipZoieDvi5C34u2W0hblRle3LJTszf5N5S65ZH5uH3C7fHW6gYidf5PyJTps9N0VWX/WHhdnzsd+FiAkZBMU2Zslfg11ymM71FQfb9pnwQTTlp0AgCJJhFzqmmVnz3uXWRBRFV8eqWrEAWNpr9Bfe/hOt/NBdAYbWgyWaxItYspiOvypT12Xf+4lXc88wqs9vzGrNontNrEImjOo2/RYq873lmFT74+GLX8dV7TuLrz67RJtmeyUZhTzNpcv4XX4HVHg6ebMKyHcfU93m0m689uwYvr3eOO/M2HUJ9kTc9L4rGLMLXKSttyWnM4k0+NHnlqs/3lqZ+C5BgFjk/nrUJj87dir8u3eV9cQiilOz3HD/tSDOpNpp2wUxX5/M3HcYX/6bfONe6v9Wn0K7y3/OqrvYY6zOJcBlPL9uN//3n6sjTTT0RV+WX/r4S7/zFq5rs/IXL2H+iCR96fAnufOqNCEonL5GMoC4BwUpQKENa/Sc5L8aqzOI/+4yV+4yvLZUVxV6QYBYx1mBhsuFq6sgXOXirDrcqM/CtRUE3Jn3w8cX4+7LdRvf7jWMWdJCxBN2yKINkJhgu42SJbKty8Xdn4e6nV0aWXpCqXL3nhOMjuuf4af9afMOXfTq3VdLmg/XKa/75xh4ck0TPF1mx67jyPYu+RcUQzHT+TP5NmRIfM78F0qWPjqkx+8yfX5ceT6l8HAkkmBF5gqqBHWmE6Cwms7Ek+6LJs+meIazzvys9z7Jk/49DTe9pRo08x9LgdEsbDpxsxlOvRacx99unXl5/ALc8Mh9/W5qdKDS2tOPyB17Gku1HPe4Mlp9Xv911tBF3/mU5/vtJ+QfWIpPhuPVnC/CR3ywxyretiDO5KIQAaRoRSxdxWx3SIAyVujbMBBLMSpwoV6gksWXLmK8+l/879Rozg2t0mlJLmAn6nG6fIX1C+UjvwbKTYupLGIfJw1TAXLr9KDYfPOV53cFTTZHv+fk1Dz+5IPjVQq/fn332LYeyGqyGgL5fpu2mMKGT39Gc09Tt8/BdtdIRt9CxmpJYD0XRmOUXTsSTftBkV+854dIscs6LoDFLzyCtjWNW4is3STArUeLogFH4mPktln3Wm3ofM4Py6fy6gj6e6nV4JWdVbVmEU0zTD1Ucb9L0Kd71y4W4LregRcen/vg6vvGvNdh2uCFcwVKGZbKsym0B5ldjGvTdhW1l+U3bRV/K3P+PvrIVAFCRs80XO1yGWJ4kueWR+VLNYuyCUxoeXgP5mBEdDlXcI39phPExM783iX6n03RZflzF9C30qq5MDCpQYy1KHCtCI37pxxuzPk9WuJi04rcuLQ2VtQVYUIr9cfN6zF/P3wYAKLMEs2JG/peUzu84KdXwBOgn1hj7xs7jzuMB00sjf1y0A798pXhhftbsPVG0vEwgwaxEiWPQjMLHLFT+JTyoWFoprSkz5PN5Cb3LdhzFN/9dMKXxjFW2cPnqOFLfnF/Va8fPzN1UmI/rMW7+v/kxpRwNfpuNqDGLG+N27Wn+NkumsPuE8/j8TYfx0toDhoUxzCvScBky5//oBj3O3ZPbjQfkJv3W9gyaWv3vNVmsIfp//7kaDzyvD4wdZd098/qeyNKKAhLMIsZ0y5qwxGLKjMAnKUyx0m7K1D2dNYvXTeKDDiTqj4MzvXf+YiF+u2B7/rdlVo3SlFnIOZv2lG/PwuUPvOxVNH1ammvnrD+IkXfPwIGT/mPrRcmv523FXX/Vh0OJC79jSXNb9oObN2X6z9DvHdBlJO7VqczWZ/8Qr/7g44vxid8v9ZWGcV5x+ZgF0pipz4nzwhselpv0b/zxXJz9tZmR5l0sdKb5sMVLw/MBJJhFjn1vteLkF11akaziC/Hg9kFl2+EGLJWtIkuw5+islOXM27yiKvqJ063YccTbz8l+/wtr9iv9qDIZa5FB9M7/+ZBqEfqY6a61Asqu2n0i8tWlfsr47Rnr8PTrmnAoMTZL36bM1mwbrA6oMctrziNqOVGbv61mkEnBaqHdxxrx4pr9ntedbmnH9B/UuY4HeQLVPRxcOrndecS9x+7WQ8H8KtPk/C/D7+4WaYUEMyI12AeV6T+ow7t+uTDB0rjRfTjyPmY653/F8Vt/Oh9XP1SnvC+/EtJ27LG5W5XXW/WYiUFjJiuLDD/ChKmmtMTH2qKR9zGrKA90f1wO1EGtCOJ9VhtMgVyGN/9kHu74wzIA2UCoqmCo6/eflJY3ynkm5/L0rnpoTqR5lDob9p/C1kPqmHtpgAQzn+w/0RTINl8K5DUsoRRmwXuuycC9Yne6nDQtrBma1pSpeL7tkhmtM233MV2QWks4VG3+XAz8+ZgV/j54Sm2y7Kxy2a6jjb5CQ1g+ZpXl2RpT9Wev/na6tT1vFtWjT8d443ufQ0dxtDf6icjJpsLCkc/8+XVXMNRDp5ox9dsvaYPv+kUfKzFmF5pYUzdD5WNoyo0/notrfvhKZOWJAxLMfHLJ92bnZ0hRM2/TIcxcbb79RNRkhJlysbff8JoBb084rIHuQ2ANFkE0ZkGQRXEvE8yMsZgyDQmqMbOCokpJs8osxqK9/9eL8Z0Z64yvt4Spco/68upvv6jbgjf9eJ7j2MLcHr0yQofLUPQQ8agYsuXx+dsw8u4ZIXOXI6tCP2375fUHcLi+xeH76UgrwKiguyMNWsQ4+evSXVrFSIJz0UghwSwAczceijzNE42t+NDjS/DJP+qjY4t4NcC9x09j5N0zMHud92qlwoc8+IbkYWQ5L5NWk9HsPTqON7Zg97GCNstk0GtXxFa6719r8I6fq/cnNMFePTKNmbgyNB/HLI5lmRH6mNmprijD6RZTTU1ISugjZm06/oW/LvcUQixTpld7VfU3u7CwVZgMve+xRV5FVRKV+dtqzVb5fz5nc+AymSIrm595QrmiD0Ztyow/8r+/9A/XN0dqYfry31e62qQDW/FK2bJFgpkhmQzHl+fqTU5huOtvy2NJd2XO9PcXgy1ieBSmzDCCmYe1xn6+GM6dV35/Dq54sOCfESbA7O8ijjAv05hZVTJr3QFM+84snG7JDkxR1pT10faa6ftxzLZ/TKoryjDh6zNxzQ/cpgbdcyS+N23M2fesqQBgtqzfqk+v/hzVR9wrGb87CJimXwyFflR9RzU5CrKAQb8qM27BzN/1U789C//1RDwrZXW8svEQzv7aTOz32G0irZBgZsjp1nYcbAzmN2PCgZPNPkvkD5Pi5E2ZPu6JEq9Bpdgrgk41+Qg8GjDA7LIdZvsXish8jixh9Zv/XotDp5qx62h2IhFpuIzc44Ud/7/890LoCXuVWSEexNhoHGoBY+bq/Rj91eeUMZuUlJC9o2eXSuNrC87xTg24SFQCT9585NHOZOn+8MUNGHn3DLS1Z8zj2THn84Xh1/O2Yty9zxtcGS4vldI6yHxCbfLlqdQCz9982GiLtDBsP9yAkXfPyGuWLewWj1KCBDNDdO39n2/swancvmWmMXvc6Tvv+Oa/1+Cse+Lxm1BRcP63TJnR+j943utlHot50GlobsOF97+EBZsPB87f78di5mrvpfb5/G212yoxmVqD/9GGbER7a7urKLWLpk/nVQ1/tfmScYfGzLmS0F50lYBhhStY6XdhSAo/Yir8CGYFraYetSkzGKpWVhgT3Sk/novm39Ke8T9mam64+qE5+MmsTZ5pfHvGOu1CmrB9x2qzqslR1BquuBXHQYtrskWajD8s3G5Ulnm5MVsb0qaEIMHMEFUHWrP3BO78y3Lc/fSqSPP77YLt2k7mV2gyGV4sU6F17YMz9ZGXZUS9JdPTy3bbfKbiHXU2HjiFow0teOiFDdLzd/5lufJeq8787t9n8kiyj4Pc+d95XXvuhQb5tpxsasW/Vux1HTd9B360m/Z2rou95fUcJaQAU/Lzus1Yss2tRe3RpcJ3Wl5hL+L6iP/zjT0ODcnGA+oViXa/SN+R/zVtbMeRRjw8a6NZggaEHXpUCzGCjGk6TWfspswiz2a+9uwa74ugXqlZQnMvBySYGaJq75Yfz74T7m1poki/mIh7Kz42b1sy+du4628r8OfF2SCjcddRWQhNoYXfgTFoTrJZvjj0t2fkx024668r8Lkn33CZIKzHi8qRW0xMt42Q6jkKpjQfeaaU78/cgPf8yh2/r9IjWOyJxlY8MnsTMhnuMmWq3oVSY+bXlClcf+dfljs0JLpo/JaWN5OBslG5+qP9HvVtkRCZW0fMfn5Atoxp8zFLmlIrr0VighljbARjbA5jbB1jbA1j7H9yx/syxl5ijG3K/d8nqTLaUX2so/oYRNWAfhxilijIZcHSCHGvagZ/tKE1dNomlOV9V4Kn4dfHzEhjJrnWRGNm7UIQxMds97HsRKOp1ZmPVQQv4dVPLdg/JhWajbe94nF1BMEsKF97djV++NLGvEkHsL0rlU9SxHuAB6l/a7Vihjuj1j+/rTX/t6otFeObKw2XESQhpXDs/L3lUL1/X0l7NgkJIku3H3WNCfHHVCtRqcuAJDVmbQDu4pxPAHAJgM8wxiYCuBvAbM75WACzc78Tx+t7m1QTEQeOHxv4VagQfcyCEKYvenXkuGeDOl8YU3RxzOzMym22bJKX8esQrgsTMNh6F6JQZzrY+hmU7e/VPbgX/lY6sRvnFP6+Ysf2M8XyK7Q7mVtl1WnM/rBoB0bePcMRWiCuD56sHHlTJnfm+pcNLcp0xHAZYTCNJOP3vc9ZfxCPzt1SuF8lHAvpXvvDV6T7Wza3tecd2dWmTB67sCJLfdbaA3jXLxfiD7nt0yyKuVA6v01XkYXDuEhMMOOc7+Ocv577+xSAdQCGAbgVwBO5y54A8LZECiig1oSEm6Y/vWw3ptz/kn8TWAztLcmApID6Q1kInFocwcwrbIf83uzN7/j5q1i9x9sJ/b9+vxSbD9ZH+h7dPma5sgVIS+WfZFpc6QC+o1Vy1Hmtrpd5fXSi2ttRR+JhORRYGtQqm8bRq21lOMfDL2U17PXNPlYgR0hhxwzue1VmFOOBKr5YIS+zdMSy3P671/Dd57x9dE3b0xf/thJXPDgHLe1q4Ysj2NjlB1md78yt/hb334y7r8gmbYFWuaZQeEuFjxljbCSACwAsBjCIc74PyApvAAYmWLQ8nqYb0enQ8GV/9R+rcKShJR8UMknEyP/BCOGfpehVYqTvuDDdB9KL+/+z1ug6vwEQvdqU+I3JhFiVqdpnM6+F8bhfVtQ/rpNrQRyTEk3CqkG3mOOqqUa02FgBeasry13aA6WGBQWBzmuXAB0qQaGxpQ0f/s2SwnWSyyw5UtSY2VGFrcn7O4Z4J8bbRQXOIXe/oSlTxcu5AOFea4vid/43OwYkU5bD9f7DTqWxS/tf6hMxjLHuAJ4GcCfn/KRpR2GM3QHgDgAYNGgQ6urqYisjABxtcgpOVn6bj2cHxJMnT6Kurg57dmcbxubNW1DXvtMz3facWuN0YyHeiv1ZVM+1bXv2I7djx07ltXV1dVhzIDuo7T94GJfe/xw+MKEK5/Z3v/a6ujpsOpZ9lsaGBmlaMurr61FXV4fm5uxzr1q9Bl0Ob9Dep0rr9TeW4/RO98bLW7dtQ13dHmw4WhBkXl+2DMe36DdpfmxlM6YNLsfkgYXn1bWTXaey7+LUqVNG78B+vK2toA06fvw46uvbPdvksmVLsXt34aOjun5zTtO0e88e1NXJQ3nU1dU5ygAAa9dnZ+wtzU2++0d9Q7Y9Ll36GvZ1L8zfVh7MlvfEiZPaOlqyZAl2dzeb9726oLAjwoqVKx1pHj6SDRC5avUqHG9yjqBWngcOZK9Zt24dep/Y5DqvolHR53TU1c1FdYV7jNp/wL2zhmmaVh/S3btzx07U1e1Xnj9y/CQAYOUby3DsWHZsOHTocD59GfMXLEBTS/Z9zpu/AD2rs8+1c6dTgPZq/1a/EceNnz5dh7kbCx/KpiZ3O2xtyea14NWFqBRmFnV1dfm07cesdr5qzRrUHNmA1tZW1zVeZbfgGfm4brHqULZ+jh4prJQ9kHvX69YWtsmao8hzw4ZsHzx+Qq5F37dvP+rqjrmOi+Vob8+OfQ31DZg7d570unnz5mP9Uflkz2QMMzm3ePES7BL69ebt2frfs2c36uoKu+I0t8v7a1Qsy30D6uvrsXGXfCX9G8uXK/O3ftsFyF27d+OFWQelfbyYJCqYMcYqkRXK/sQ5fyZ3+ABjbAjnfB9jbAiAg7J7OeePAngUAKZOncpra2tjLevuY41A3Zz8byu/njuPAYteRY+ePVFbeznm1a8FdmzDmDGjUXvlWZ7p8hefAzhHTdeuQGNDIe2ZMxz5iKxq3wRs2ogzzzwD2LrFdZ/1u3nNfuCNZWgsq8G+hnr8fVs5/vtdtjRt+XTddhRYvBDdu3dHbe1VrrRk1NXVoba2FtWvzgaam3DuOeeg9rwh8vJrjgHA8DETcNV5Q7JRsm3HR591Fmprx6DL1iPAkuyWMBdOmYLJI3q7yjN73QFkOHD9xEH46MwZWLC3DdsfuM6zPoFsuAwsmIuu3bqhtvZq9z0znXHl7PVdUVEJ5D4QvXr3Rvfuzfn7Vu0+AWC+K79pU6dhK98J7NyhLdv2BduAdWsxfNgw1NaeqyxL9fyXcKql8FEdPXYcsGY1unat0T63jJpldUBDAy6+6CKMGdg9f7xt7QHg9aXomWvvqjqaNm0axg7q4Ux0pjwu3yWXXgbUzQYAnHfeecDrS/Np/mH7a8Chgzjv3POw72QTsHa145kB4O97Xwf278PEiRNQO3lYPp/LrrhKu8qz69I6Z5/TkU/zCvSwxxTLHR80aBCw1xmV37TOrT5kT0/sy2eceQZqa89W1ndFdQ1Q34ipU6dh5oG1wNEj6NuvP3DwALp17w6cOunK99JLL0PbnGy9X3LZpagqL8NPX96MwUM5sG27/DkkY8L6/SeBBfPQrZtz3Dh74kRgxRv567t06eKqk66LX8bRptOYdtHFqKkqB3LlsdKv23AQWPCa41jV3BfR0NqKCRMmonbSUFTOfTHf98S683oHFbNnojVTEGbE6/n6g8Cy19Cnb1/gcFboGDhwILB/HyZMnACsXA4AuPrqWuCF51z5jz/7bGD1SvTs2RM4ftyV/4CBA1Fbe0HhgKLc5S/PBNrb0a17N1xx5ZXArBdceV1x+RUo23IYeMO9rZ+rHnT1oxmnL7poGsYMdPbrzfO2AuvX4YwRI1BbOzF/vKG5DXjpBXUZdCjGCjsXXHghLjyjD+rq6jBuwFnAGnfIqsmTJ+e/GdI+hlyw7heyQYZn72zD7J1t2PydN2kXIsVNkqsyGYDHAazjnP/IdupfAD6S+/sjAJ4tdtlkqNSdzOsCDyxpPag93tSvprByTX19FKrnMCl89sk38ItXtijPO30K5Hz8iaXa5fkmBHkVjmoV7n/LT91CGQCUlfmrL69rxXdraWPD+JiJ5lEu/K+830deTud/dXpeJisxwOxDL/iPw+dFXD48h041455nVirPe71DyxWCSzz2VPVmr/dMBvjuc+vw6/nbMGPlPqMy53PROKN74djf1We/i8IC5eVjZlW8t+new9VFcdx0rFFdJvqzxm2Vkz2majV/3GZ/x/cghIJLVsy2hH1Jk/QxuxzAhwBcwxhbnvv3ZgAPALieMbYJwPW534mjEpzCRoa2GkWx7PG60ia9KhMAXl7vVpAGWS0ZZA86cY/BoCzZftSlxpdRxljgALPy9Jy/w0T+9/Ix88JPFeqc/+3Zq96pdfTx+dvw8vqCSVF0Ro6CuD429/9nLZ5c4r2frYq8YGZ31/P0Ryr83c55fjeJoAuRvJqZrO1YglF7xt27OefStis6/4d5I15llp32k19hBan8fJC6ttfjLY8UJn0c3Ci9k03uRTgnGltx4f0vBdoiznpzroVCsbtNez+rSfWO+1/3llxJ+50lZsrknM+HWk64tphlMcF7H8dwFK0haAaiKOKYxUHeKd9HHQWZ8eQDVgbRmAm/TzSbCGbRhiYQhagw4TJU91rVumLX8aypQkFQIVon+Jm80v0nCj5Nqo2jTfJS0aZQmYXtM2EnZs2ShSReadrr/eGXNmL7kawgq7rteKN88YY6FIQ2ewCFyUQ7d0f+V06Gc/9HEy7Dn8XBecz2d8D8/T4C1+TFuVkf+eozbpPfit3HcbShBe/8hTu4sZi/SGHRmHz88cOOIw0Y0aer0bXNbRnMWX8QDNF/s5Je5JO483+poGpkUTWIuCLG55M1ELrCfMjz+cWgTBdXmZkQxDSc15j5vjMYzFBjZuF1rcuUECJchiV/uD9chUJ85Wm16S3ouKa7Tfn+bYe727YuMo1R5Ye4wxEExa4xK2iY9dir8+/LbHuXSq5tbc9g8rde8kzHcdygJzm2ZBKub8twbds1bWOH65tRWV6GXjXu/UY9LZmawfAvrxU0nPayjLy74B/lVUTTcaqwAtXrOu/0jtS7Bexu1WaiQFhT5pNLduKeZ1Zh3bduyvoU2th44BRueHguvnTjeKOy/OjFjVi64xgGd2U490z34htA3wY3Hzzl8pfLl70TmzJLCs8As1z/2zv9YA3BVIjKmzIVN8xYuQ8vrZU3bj+EnWjISvfA8+t9p92q+IK+svGQ9Lg9/Shm4iavpZwxIyHQ1JSrmrEGifxvH+Bf234UI++egdV7TjjegRW/SH6/eV4mPma6c/Z66V5dGOzt/kM/m7M5twgjHKqZdMKWj3y57HWR8fiY+2nnrZqNvlW4xkTJNbq9MtsyXDq+FSZqZuWY+u1ZmHL/S9h1tBG7jjbis0++kQ9V4+ljpmHh1iP5vz2FUAM/PxO4Ointlkz2/iwra7fqctcxeR4SzaFi1i8ry8/mbAaQ9akUsQLovrbdzJxqaXj3N3LMWiddI6jtmNf9aC52KcawIK4wUUKCmSFqHzPhd+5/v5ojv+1A1v/sMzX39TltmOL8Z/78On6/MLs6MIzGTLbxdVT40pgpfLw+YourpEo/iGAWdMGAkY+ZYXplQm+2NlQPJJjZ/rYE9vmbD2tbtVNT4MOU6bhUZ8r0Npl1rSrM/O2C6kMvbFAuwvCDql2F9UuM6jNgL4b1cVG9C5OPuCxd1TlxYmAyWS3T+Ji1tWcUi5uyx7zitDnSynBc+f05uPL7c/DvFXvzvqxe/pf58TzgC/L2MTNMx5qc6WyZ0Aht9nYhucZ8EZn6mJiG7ForALJ8r9/iO9Go4p4lbcokwcwQL9WmygHSlLiiD4tmDZPyhekgUWjdVPipoeOnsw6ufibEVvpBXoX4kTOp5+wt5pl5lcsV+T8CHzPA+XEyrRt/JlozjZnJR8xeB36Cph481YQth+TxvuykVWNmwVHov15j1i/q5CugfU8SFU+/6aB3feZ9zCSR/1UaM1vGoTEdH+ZvlscPzBclYFn8jvsZzUNzztVBmJU/rENm5dAVV6xLWfurzAlmOg1sHGOMMg3FcdKYlQiqRhCVlO+3Hfj92Ba2W/K+0U/aqw61aTfdfWT2JsxeF42w5mcQm/6DOgD+tEV+ZuAuhHtMctWZJZyJmT2D28csuEOUwwxmXxkZwwTC3vZ/OXer5jpvjZm9jfgxU13y3dm49oeveF6nEna8qqWtPeNYMRoX9uf3as9/s/mVqdKwfgf5kP5b0J7LPv6OVZmiKbNd7mMm+pyK5W1sMd9eKog2OQgqwcdUM2P3MdNuyWSgBZVdYywMCXkv33UcT+fakXuhkEQwywVulbYnQ9/IQln8XSPXBId7L3FBgpkhXi/K6z1uPliPTRoBxq+zod92UzA3eF/rZ6j64bJm6aa7+fMvbcTHnwgXV8zC/sym46nXyjxn+vKB3uhe33cA/1oerdlXtVdmMB+zwt+FrarMDZT+qrBw8YpdxzVpqj5I8uN+Htu0+9k/Ni0+tlH72Zwt+NjvlmLOhqwJ7dCpZmnYAovFNv8lwCQURe5/RVnD8OjcrUrHfzFPOyZjmiOOmUBbJqMwu2VRJf+ZP7kDrIpYVePVN6SnNeY89/05s6uiqShNnJq605uVvTW6Tp9OtfBuMg6+7WcLsPVw1tfLxJSp05j5HaVMyveBXy/2SEN+nJz/SwTlqkzD1nTdj17B9Q/PRSbD8frOY8bp+92jMxKKNIv0S5C+4secZaUfJJ8gH8GHZ2VXFUWFasYa5HUWYkRxh3+LcRyz3KdgybajeGHNfu215kKRqqz2fAtYH12xzN/+z1qtP6aI5ZQMFPz2AOBr/yzsQuD1CFYaB09mt4+a9p1ZuPyBl+UFB/DeRxd5lsvLFyyv9fRMSUhD+P3063LNmlgOsZmZ9AlduIy2do4PPq7+sFptTMxl8TbzWFxi37DeT7FQ9SdVuB9dHF7OzfpIRtpGzLRouldqojGzfMyaW3UaWNMxxh9+huikV1+TYGaIl83Z9KX/aclOvOPnr2KOEEj1dIt8jzOvdP36BpgEGy2WWOZXM2Xqi2THj4+Z9Y6DOf877zEVhlTvXYZXqdwas2CC2fr9JwOtwrNjVcd7frUQ/+8Py7TXmtR31n/G5LrC3+V5wcx5za/nb8se90wt+36ueHCOtKwLthyWHpdRkdcUFK5Tbc5tijxLvcnKLGHnT88V6Y4ycelxFc4As847VMKJ31WZOsQ+c9F3Zzt+GzvFezytX62ieFwlhIrXqF55RvFedOZuv+3HtfOI5NmsLdKa2tzjnt9A2H79wGRXq5IgU2aJEMWqSQDYnVueu26/c+861SDkla25o6R8VisjrMLMW4hVDwbadAP0FX8+ZsHzEZ/FNFcTPyjTtMRHtQZGP3WwYf8p3PTjeTiZExo4d+avemcuvyTjHM3bgZFjsw1rlaqJb5oK0VxpEktNRoVNAAmCmO2hU82OLB2r9nLkV2WG/MgE1dq7fdXc1zCbKdOlMfNQWyjNdgaPy8HxoccXa0O+ANBq7PzkabItlh1VuB8vrbXpJMfketkZK/+HXljv8i12a0zd91v9oEmjMTMlCtFJ1cbi3onHCxLMDPFelWlGz1yQw+/P3GBkTuGcY9OBU/j2f9YKs1F/HdD6K2ofMxmnJVHI7cj8YbzgnEufxwuZj1l7hmPk3TPw63lOR/NCnfrvlEH7cUW5vLY551ofJBmiAGZpvfzMRPdLTDmFj75Tq2FPVewefoQBk0EwG4zX+0PsKJ+lMQuRb7nwftRymfvEDQ+/kheOLAE86B584l3Tf1AnN2Xa/o7KlOkleBX24XVe69b6uCm3C2bCuTZFaJIgO4GIcA7M26RfaekrvYD3KTU2wrMX/Dw1eWmENkcfkfytMlvuOX5ayILj5Ok2/GzOFtzmYW6XlcXyMWuWacy0qYVHVh5VG6NVmSWCqsG74ph5fAx6dvG32QIH8KHHl+DX87fhwEl3zBWv5hMkDk/Y/T8bPFZF6fakVGUdYI9jAHKNlCWwfP+FDY7jukHKi6AzrApb+ez18cSr23H+fS9i55FGqTZEhsqUECYCvj1Lzp2+F85zxdCYqS7k0j+tj34YjZlYdcoSSE5sPFCfj9dUmRPw2gQT8Qtr9qOpzWSS5fxd39ym1GhYzSC4ds7sXYoTLMbkgqEO56pM5w3epky55BnH7iNeBNVKqu57dN5WTx9C1znotMrySb2VnqyP/PONPbj8gZcdC1Hsl4nuDqpwPXYqc6bMtXtPSoUzMQ8tPqtcdrlKY0amzBLBe1VmbtbokY5lYzflb0t35zVQMqFF21FtwozVGU3MWmFnLl6r1YLopTKCj5HpQKh9XiEJXYDZuOLMlYtRYXO8lAsxsuNog83PRV8G5SbmPsojFZYNZutujZmfPM2u8ytnlEkE2qftWw+ZmH0M81IlZX28rPcsChv/7w/L8NvVzQY+SvqPtOwDqxJcvBAv99wn2FEOdR+VmzKz/7dzeYBZ03xNjjuu8b4EWw3i2pmiKpNKeP5F3RbUbSjsUmL3MdM9n8kkxC6L6LahW5QTyKxVlwAwc83+/Mpi8SaX8786IgYem7cNX/m7c0s30x1OLKIYkVsUkyJalVkiqDfU9SfGtCpUpyq++o9VOJELlioVzDTNU3bGyJRp+EiqD5uXYBbUuV72Cg7XN+OmH6u31vDl/M+d/8vOqRBPmz5hua0HygZPP/5hKh+zMBpQzp1BPu3v3OF7FrgGzNuDyrzgNGUC3XJ78Mkuv+tvK3yVUBbTS1o2la9Qrr8XNGbu6w6dDiZJeAlrQbW44m1q8611nruOZfP3zku3JdPqPSek9xTCZcgzaPYRxkTHNYq4dvJtieR4lVVXR00Sl5DsZFvdD7zelfi3znph1WOVbZD6Rd0W3PmX5cr87XjFS3t1ixASxue31P/iMfcxpY8ZrcosDfz4lujwmgXqCBPM1pcp0zAf1aAi225DLMvuY41Y6WPvwuyg4/4APLt8L9bvP4XHcyvtRGSmzIIiwfkAKo2ZyYpAE+2AF87B063t8kpTtSozKuwaWNk53W8dxoKZz0q1tFNhTJnBxc0slsasIq8xCxa/SZav1C/IdmVwHzOu/W2nPcPxzX+vBeAeN0zaX7ljUYTz+vty6Yrk3UUSUmrI9mUMWhbfwoXHeaO9MrlZG7EEQ5WVR7zHPW6al8/rPpP8vWhtz+CIsAWTyscsaVOmP4enTkzQiN8iQZ1/AQiaC+/r5c7/4bz/3/foIuw61oj5X7lGOdvw0pjd8sh8bFZs16ISCjPcPaM+cboV9/8nO3irBjiZxkk947Rmj+Lx+FTbbjOQ8NFh5hpM1SbmocoH2AypasnMVWc+8ggdx0woh/Xb2vkgqkmVmJajPyqut/qCtchD1v/Ntu/y/7XSaUP0eTl/q7QHnHOs2XsSa/edtB1z52/Rlslg4ZYjuHR0v/wxa96U0Wh7lOUMYcwK45ogHd88klOdXrH7BH42ZzM+M32M/n5u+1/Tnk00Zo73Yk9XIK8xM3S/EetUJtzoxqSgu9mYcscflmLBZqeWTqVEIFNmieDHzwIAHn5po1QVbWLK3HGkQXpc2m41ydlPHTrVrE5Dko8q0OLCrUew+1h2pY6q8XoJZiqhTEdGEI44Bx6zbd9zSLEZrayzK0OT5A7LAmXGNYHyEjb8aElF5WAkghmHoxJVad726ELH70/8fqlRBHZdmv83exP2Hm/yvE61WtlLY2Yy9uqqUObjJWJpzKwyqjTmXq8qiBahsIl5PHC4P9oyx3KL442teN9ji7DMEVS5sEDDbzlNNIJx+Yaa4lqoIOEhYRGSDo1cll2c46EdfuLV7dh4oDD+Fq5332d9v6pVGjMPQUxWFnuf0z2HCX5frSiUAeo9OylcRong90U1t2Xw2wXbXcdNTJlv//mr0uOyEoRpPjot0+9e3e55rUrA8bNVjSmi8z/AHaEwnlsljy7fs0ul65hVPrdPhJWyEw4Dwdzjt/I+hX+OhR8tqSjCqdT0QdGZMlcIZunjja2YsWqfUboq37EfvbQxr43hPoRj67p2D8HEKD3XNcrUpEetiVhBSHRfE6kp06GxMkjYIC9d2xc/2jqNmcWR+mZkMhztGfuuEubv10TYkZUnTnR+X9Hmo0f5znPH/7R4h3B9ro9I7rOCwJpqzExC5ugE5bjDZchQmjJJY1YaeG11ke+YttYlWw7cavDCjza0aPNyHlOnx7m7sS/fdRwf+91ryvSArNnFZJWdPdaOfZAM43y7ZPtR7Dtx2nWcZ9xlELdbkgmEZ/br6jpmzQRVHyCZv5hfwTzIrE+QO/OYDlii2bawcb05kqHUsSY0jg+diT+HTjh2VBsv9EVLGFInb5Kvuy3IUHVra0ZuDfRRBZiVlU08FvjjYtD3reOVNsdw1+ITzXv93FNvYNz/Pu80ZfqcZhq5c/hKMTgmJsQw2IVRXV7qDc7l7U+ndbS2TVItQHKNn0LaMh2EiZa5mKsylRozEsxKA6WPmdA8RNOTqCEL4/zvN8CqqoG/nNsOSpVGhcxhXnKdSmN2e07wC8qn/ug2gWU4dwz0nDtXNALAX5bukt4n0pjbBsl0xR0H91ylE1RgUQsbcqHqM39+Hd97bp30HhPn/6bWdnzg14vw87rNeNFjD0uLfLLczzbmTn6jWJwBmK2AMhWO7cKjV+R71di7+1gjjqkmR8ryyc9YPixWX5H5tBj5mMmEMA+NWdAdNsQy6j72pqZekf+s3JfVmNlNmT41ZkbhTjxMe1Hh1S7C5pdXAGgEWJ3WUdQim5TPmmCbLp5xC33u+8Rj53x9Jn5RtyX7wzBeY6EAhtdpUH3DyPm/RPDrYwYA2w83YMy9z+P/3ndB/lgY53/ZnWEEe9WgVV5WJtEUcIhigsPnK3gxXMj2j3SbMt1R/e2bShfuc6ev2qNQpxWNy+fAuYedU/AEnA79HBwzVqrNg26NhfuaFbuOY8HmI3l/i+0P3KwtX1bryhy/lRlq+NZ/5CvsgMJEQY88XIqrTDa8NGaqd3rFg3PQpbIM6+9/UyDfLjutuY+bNSFrDahNlmvM9Mei+rjoxhhTjaIK+76XxoJZXpiz8lTfGKQGFm45gvc95r2JvB0v4aVYvm7KkDK5/8Xvj/VLVr68j7Rh0cWsvXzMAKChpR0PzlyPT9WO9h8uI4Kvjqo/Jm3KJMHMkCBL7i3/mJmrCx/TMP5XTlMX15bLq2yAur9VljPXvRd86yUM6tXFccy+KjNK1W9lhVxjJzqOmsT44tw96NQ3t+XTsKN7x75Nmbn/v/GsW1gU05b+nfu/jNk1BPo8XabMfByzwjFPfxHtR1ioy4g+Nr9ZoNam2bNSazTt1xWG6/qmNu22Z7riW3v5iZeo7rEHA7Uj+phJV2V6lEWFyofHEuYLZqpw70lVthfWHMCDz6/P/2aGeUmGsUDaWCNTZoBH9yuUAd6a76jIQG9aVk9ect8LhVZLdpulMTN9Ar/hMpoVW/cZK8wiqFqVaxE5/5cIKgskF/53nJMc9NqYV4dTu6LOIyxlZe59CU81t7lWU9pnFV6aQHFfSh0Vkmj4Gc5dg4roYyZj1roDeUHMot62Qbed/OxWSGPC12cG1kw+sXCH9ryYbGt7BvtPNBX8w5j5ykxVgFk7fnee4HAKhkkNVxz6sA3266xCqnw1Zfepjpmau1WIPmZeMf5UyPLdccQdVNl+VcZDYxgmbwD43JNvOPdSZO4JnRf2RRF+TZlmpu0iCUzKtmnlp8e0XXn1QfXzZnGvnCykK9KWX1Fslpf4PmTjj/0aa0cby3Um7nAZMlSuRSE8jiKBNGaG+A0wasf+YQ2zUs4x6BpozDzT09xqIojYhTGVE6XFt2fI/aJkVEo29ha1VpzLNyiX8cdFOx2/65vlm4Pr6jI+53/nhff9aw3+tHgnxgzsnjtSeEavOjbxMasSHfMMUAa5Dbmnqh/8aC2NnYcll3ltvO23t4k+ZjLTiUk1yvrjLY/Mdx+0XWd9hEMLZuFud2F/XCvWXJBxzOo7DRLXh8I1vpMNhMpsbB31er72DM/HutOl4/U8XuZ+lx+Yxg+zsBOK4tmEw0Y+Zrbmb/UJVzgO07HT7DItqjE1aVMmacwMUW8H43cGHUaQcgomgLcpM8jsCoazVz8aMz+oNGZiZ9GMYw7ED58sng3gJaj6FMwAbDHYa89hnuUFk9jxRvc2XCrfOAvVqjj7xEAVYPiGh1/BI7M3uY47zavujaaLBdf4mAkX+kjTTdTjcXNbBscaWvIrmIP2E1Nhc9HWI5i7MduGrDwV27Ea46ft+326IBozuxZKtW2TeG3cmGwXpsO0XXCovznffW6d53dKGcNRckxn5pRhspJf1o6rK7NbqCURLkP1PSZTZongFQjU+t9r9hvGlGlvK4XZjOZ6jy6lU1GbfAjs2r8wq01FKiXmNneAWS7dbkmG2Mn+s3Kv0XVi/n6YsbUV1yr22lPlycHzpsaWXKgVu9+OTjDjnBtpzFSD+sYD9fjhSxul51JhyuTqsruFR7M0RRM34O0n43e8/vGsjbjg/pfyK4ZlM3QT3yzTfH9lC7rcnMsrzFZuQGGSYEJQUy839DGzX/fIy5vxv5IFP47rlSsYfRXTE3UQYzOtpT/BTH7u+dX7pW3aug9Qa7V0/mAmvp2ALFyGWgtnxxULL4TG2y+kMStxlKpqn+8vzAsXP0DZY/r0ggzJPIDGLMp2XCkRuDIZ7hi83vvoonzYCy++P9MZWXtYnxrpdbpn8Lu4YdNxs7KJ9WyZcS0TmF3D1awRfjPcPSnIfywMtg5S8dr2o44yJDVecZg7WIcpoksQc6XtL/Wth5y7eARd/BPkmfKBlIskTmcFTG/s11iTO9NwGeLYtHzXcc/r/RwPiufE3SO/dkNLilc6stiZ9vvczv+585I35xWgWUTsn/JNzN3HulSWg3OeD0hdTGWVyrWoZDRmjLFucRYk7XjOBN3fQEU6Icpg6yKFjhZ9XjrthB279q8mp46OApmvBefuTrRwq9wk6YWXE7lu9mhKEB8zzgsBOy0Vu33Fnk44zGg0Zku2Hc3PpMXnGHn3DOw6WnAiFwfo//3naqzKRfXnMGsXcZDdSN7kunD5uN6zmF7I9IPvlRk8zxBKei0yjbXfclqr4jKG2lidxkh1fTFQ76VsVoJWyUuyL6xoMVwhqZqsikGXLX5Rtxlt7RnFmJe/2QhReSG7TaUxm73uIH7vsVAqDmT1DpSAxowxdhljbC2AdbnfkxhjP4+9ZClDfFGFVYbBVPdBcGjMcj90sYq8SqY3ZXpjj/A/om8NulRGo4CtkDioZ33MhMCXAfuO6h3ofcyC5eWFGALEEszss1XrEnsbFD/mnLv3yrRf/+zyPfnrRDbsP6Ut45GGZuW9xYJzcyfkMMJj3DNllSnTm/Q9k8mqaC/szv8m760948/P0dQMF5agi8PG5hb5yASBb89YhyXbjmLZjqP5Yw8sacLzq9WxDBua9RozMZ+/Lt2NS773srY+VM8man+ttF/bfhSnW9qNJ7jVFWU41lhYQV3MYUY12U29YAbgYQA3AjgCAJzzFQCuirNQaYNz7hpQrVWGdkdUEdm4FcqU6ShT9v+gg+6Yrz6n9b8wSfa0LQ7NxgP1mDayb6CyiEhNmZy7ZntBn131DgrOru7zQeOYeSGmK65I3WubNduvlW20Ljr2OwV5eX4mFNp4fJu5e5ZBk7f4nNbPIM8qTqDFFP68ZKdrw3Y/qEyZngr5MBqzmF6auKiAmdoybVhacFP/xbf/fAH2nmjyvjBHsZqrZ4BZyblzh/XEJ648C4B6srjxwCkcONnsOPbDF+W+oABwutXDx0xSzsP1zVphd/G2o8pzdtozHHuPn8a7f7kQdz+zUrvS005ZGXMG0i7iIFPSccw45+JeN2YONB2Ek6fb8N3n1kvP6V6f7N2a7JWpwt5YdPFnCvmrT7Zlgu25ZkeM0P+OC4d53mNCpVRjFt0sRrk/WsC6lF9veJ2Qh/jsn/7T68rZrpifTFgT85GVy/jJePH8lVxZ6zRmcD6nddmmg96rYkW8nP//s3IfFm01+1CJlDFVgFmzQMlBiWvyLwvwbNI+7HdZfTGjGY/srNl70rR4AID3/koeLLa+yXxBgwkqc7GX87/ltqHq24y561lXTWqNmb4cujQftS0o0dGe4fkFSs8u3ytNUx47UAjJY5RbNKh8+5KOY2YimO1ijF0GgDPGqhhjX0TOrNlZMFlurv1w21qdaI7zg0MzkGu+2nAZAO74wzLteVU+XoN5JsNdgtnbJkcjmMlMmc8u3xOZxky1AkqXnt8wB6ZXi8FRZc+e34BY+64lPmYSlVmQKrPfkpjzv0YwixKXYKZ5k34teT26VMonBQH3yjRFNzat/daNgdMVTZmmOxjYL7EEkux/0b/fdfvkgtx9/1ZvERaEIDvDMLC8n54qbEMZYy4XBV01ybaz8yqHV5qmtGecTjCyUCbSBQEoakhEB2ndK9NEMPskgM8AGAZgN4DJud+dBllcLQvx/dkbmKwRholjZu89BdNUiNSUjc979trOORqFLTVUMbL8IttE/ZGXN7tCcgStS2UsH51g5jMv034txjGr0gRns/tDiHUtW5Vp6uPhvWAlJ9Qp0iwGHN7BM7N/hyugSSymoHSvrkBDcxtOCOEnTHpNXBozk23NVJyShGbwW8xWn6sy00oQ9wjG3D6lrmuQ1T6Z0qgwZXoRhSa8XdB6Wtua2ZHqJTh3jF3FaAe3Th4KQK0oiXKLwSB4Rv7nnB8G8IEilCW16DRm9o+WiKyzhYn3lZF8gMLslan/0Olvbs9wNBmGq/CLKj6Z2NGDLqSwv4NXNx/GZWP6A9Cb+6IMoGtHFCRkZty8KVPzQjPC4GYdy6ch/O9I36OMlkxqGmsqDrihc3jY0ol5HK5vVlzpn+7VFdhz/DQmfetF3/eGeS6dCTyMYCYSZGLWYotjlvC3MBTezv/uYwywaczkY1kZY/kwEvm0NK2h0cP530/5/CK6x8g3MVcJoDYfs/BF8cTS9io1ZmkXzBhjv4WkrjjnH4ulRClEt/pIrBjH9kuSlxtVHLOM7WNpXDgBZcwbeHfU17YfdTj/F4OGFudsMOj2VvZX8P5fL8b2B27OHte8G78CtWnJ7Fmu33dSYcrMXasLjZJxvzNnQF4rP/91ZrWxptaMKyZcsdBqzOx/R6wxe+tPF4RKz073LvLh1sRnPi7nf9Mgzab498UsmDKTCsUSBargzzrnfzCWX+yjXG3q8/WoxuSoAhjrEE2ZsnYn+/6t2XsST7++O3wBfGC1+3mbDkvPJ+38b7JX5n9sf3cB8HYA5rrVDoDJ4MU5cM8zq/DkksK+jNaH3unsGkIwszV6S3sSJkaR2h/B26zwoceXYNKI3sEz16CSgxsE00mY0CMydDKz382nzU2ZhQvf+6jcUdlC6/wvMT/LTHxeHz/Z6ZW5OGb/VuyYUBS4ZrAUzMFhiHNA7lqliPUXu4+Z+lzEcpnvUhZ8zJLSxUaDSrNaCAQuv688Z45py2Sk44/s9ejep2qy6qkx0582oi2T8dSYSa1IGe4UkIogFHl901OvMeOcP23/zRh7EsCs2EqUQnQqensbsgtlgFxjFtmWTLm0vRzCdfxEsjdi9j5g9voDnuXZbQtMWgzEzYqjF8zU9eU3YruxxsxH1FT7u3avwHS/b3nkbXfyyk3KBcSteYrpr6vbK1NclRkG+4B8zzMrQ6bmxLVZcw6jeoxJYxaVX6jFN/61xtf1duf/ElaY4Uh9i/R44ZnkD2eFBmprl2vM5Ctf1agmkF5VG8WEpF3YnUXWX+NyCfGLp2BWAs7/ImMBnBF1QUqVRbno87otLexsPOB/Cb+FvfNYDVynAfFqW8+8vkd532HFQGNH5g8VBarwAY0tosYs2s5jr68X1uwPlZfp1SYDVcGUqb7Wa3aaT0OSBFf8nSZMTV1hPzD29/HkEjFKkBO/WekWEXkR5qmKZZZhAGasLPhD3XndWM97Cqa+5PwXLQb2qA5873eekwcq8AprZAkIbRn5xGPjQX3wZ1OCaMr90pZxBgGX5WniElKMVuAlmCXt/G8S+f8UY+yk9T+AfwP4SvxFSz/LdhxTap2A6GcH8zcdxvM5R9CMbaYZNaZJVlbEozNRTeJFx9YoN04H7CuogP8nhBmRaef0ccXMatHPgOjQmElWYIppiSs+TcqVtG+FCq4xZXLJcwZl+g/qwiWgoVKjMfN2zg7+YEl9Y/57+hjPaxxxvhJuelH729mRPRpDITxOVjBzX/WrV9wxxIK0BfPpX3DaM9wxgZWZVdOiMfNa9JJ0HDMTU2aPYhSkFDl0quBXIOsrUdupv/d8Nsjttu+9Od/AveKYBcG041dXRLc/pgmi839LxBozq05l47NMMNMtfjAtmYnKPL8q0x4uQ3AZ5xIfHfE9ztlwENuETbXF61Iql2VNmao9Tm1/F0uwDPJxlO1oYZxf4DuTc6o3WfFpNelMJml9WfgVqoy5+0/Bx0z+dBV5U2a8kkBRVmW2c8cYFXTxWxrGoKRNmUrBjDF2oe5Gzvnr0RentDjaoDf3Wf5kUftx7DvRlG/gdRsOKa8LOiCb+m7J4o3Fiagxi+qD8/uF23HbtDPydSoboJslPmaiadVZNrO8zQaqnBCuNWVKVmUKB27/7WvSe+1BiNO6Mk6vMSt+mYNkWaGIURd2E/Oq8jLt4pRiOTKLH2KT58ovYpK032Kjej+mdKkod03WvJ6pJrcg5HRru/GkIlg1eZgyA6XpJMOdWxfK/HLNXDfibwhefSJpU6ZOY/ZDzTkO4JqIy1JyfPUfq/J/6zRmUX84TjW1xTrYmvpTxVUG1fAoasyimtV8/dk1+Pqza1A7foDymjd2HnMdU61qBeKxyoiLH5z5uXO0Dy6m5UmnWIZcuIzkZtuV5czRL4Jo5mShUCxmrdMvttHl5vUhK9Y3Zvmu447fJhNSezzGpHVmYU2Z1ZVlLsHM6wPfrTr7CW5obov1PWV4dgKqIjofs0JCsslC3JpBU7yaZmo1Zpzz6cUsSEfEGsijfsXNbe2+nMb9Yqoxi6vxqjqN+Miqfc6CYmkfZY8lcwRv1AlKERbNJKk7n1ruNmU6ymNWoLT6mIG7naOfXb4Ht04eVhRT5gcvORO/XbC9UJwAaVQpBDNJgHQXadVkhsV6p797dXviIQoqQyzOAOSrbrnwvx3GgG45jVlDsw+NWYBq4hz4v9mb1edj8DGTfUdM9oouRlP3yiPNGrM8jLFzAUxENo4ZAIBz/vu4CtXRiPolN7VmYtUemIaGSLrxxuVIajpAak2ZURUGivcoCK+Lt7k31g7yftL6/ZdpzP7nqeW4bHT/SJ3/VYjmbXFxiAkq07/pjgaq69L6zkywv9M/LNqRYEkiMGVWun1uredT9cWuVdlPcGNLW6zvMSt4qTM41hh+U/e2TMYhXIuC2Yb9p3yHHUqKpCcJJqsyvwHgkdy/6QC+D+CtMZerQxF1WIemVjONWVBMNWbbj8QTxyxK/6w48y+WxiwoQaonrRqzrI+Z7Lhzrh9X6cVP9svrD/pOQ7Uq06jMXO7naHx/Qvz6w1O159PU3HSmZhNkGjNLIFM9ZlVFGarKy9DQ0h6rVlS2atvO1/65OnQe7e3cEaeztc2Z4S2PzDNKpygaM68tB0sgjtm7AFwLYD/n/HYAkwAED/jSQdF1Kr9R471obssYaUOCqqejFiT9Ypp7XJ3HVDgplo9Z0LTs9ZOmD2AQVHtlit0gLsGyLIKFLqpVmUYxhsGlgtmIvjVhixUrMreEtJplq2LQmO20gnBrHrlrdXnsPmbFqPK2DHeEyGgWvnum35VitA6vuk7aGmQimDVxzjMA2hhjPQEcBHBWvMUqPfaeaFKea1HsSRmUrMbMW9hbldtKxy9RR9T3S9IaM9OPexyhSqRpSfIx+YQ4wmAYlii1GjPIy9bansEKu9N5TMWPYmG1KiDzgQYztwTZ3rZ9u1alVtAB5PWm6raVIQWjsJgGAP7mW8+RHu8iCR/0z+XZbcx0b6hbVQUammPWmBVhaUU28r9dYxbsO1KM9uyVR2o1ZoyxnzLGLgewhDHWG8BjAJYBeB3AkuIUr2MQtV09qzHzvu7jTywNlH7iglnCxhlTeU9bTTE/gomgIAsw60Vav/EZLt8XtklcBRfXghSJKOxXWFOZyo41GwpmklUCZWUs1aZM2cpM1YRKJtgUE1MfM9XqzepKtWCnm1x1qy5HY0v8GjPTvhFUQG4TtmQK+h1Jg/N/0otHdVOETQB+AOAWAPcAWATgegAfyZk0Y4UxdhNjbANjbDNj7O6484sTlW9IUEw1ZkFgLHpB0i9pFQ5EdLOqlhT4uNo/gDp/ODt7j582Tj+K13TzeUPM8uLyyOhi34rNxywSjVmYALNc6hIRNihq3MhKpxIQdIJNMTCNy6h6j0EDbnetqkB9c1vsmqK4x9V2wZQZ1IUnqslVF62g7FGGtJoyOec/4ZxfCuAqAEcB/BbA8wDexhjz3gQtBIyxcgA/A/AmZFeDvo8xNjHOPOMkakGnqbUdcbmBlTMWuU+cX+IcoKIMiluszhtFdei2DrPzgxc3GqcZxXvyox2VZSea9+JblRk+jTBtT6kxk0SbTxMyjZmqvMXeSUTEdO/fcoXJM6hg2b26Ao0t7bFqzNozHCdOm628VO1VbJKHXUsW1NUkKsHs+++apDxX8s7/nPMdnPMHOecXAHg/gLcDWB9zuS4CsJlzvpVz3gLgKQC3xpxnbEStMWtuyzg2i42SMsZKxvk/CFHuhxdk4Dmrf7fQ+aZFSRLF2OXHxCobsJsEYSU25/8IKl21KtMEDrmPWdS7ikSNrHSqfiNb1aji4lF9A5ZIjalgphKwdaZY3VDRtSrr/B+nC8f8zYeNrw1ajvYMd7gWBO2KUXXhS8/qpzyXdud/zzhmjLFKADcBuA3Z1ZmvAPhmzOUaBsAe0XM3gIuFct0B4A4AGDRoEOrq6mIuUnBONZibh0zYsHkrTpxsR1U5YGihMobzTGD7elTvYPeePZGk85nJ1fjZ8mbHMcajE2jXrlvn+56GRv8hRjZv2eI8wIFMTIK5H46fPBU6jYOH1FuK2dm8ZQvqG9wz/tdeX+74vXGjucbPDzt2uGNsNZ1WL/iRsWVT8LIdPnwYi5e6F/OcPHFce59zR1U3cY6bdXV1WHPYPUCp+k1rs/k42Q+nMK5PGTYei64fHDlsFgJlw3p5+Y8c2q+8p73dXQ8nT55EXV0d6o8348iJdrz66kKzggZgy1b3Zugqggolre0ZbNi8Lf+70Wf/sDjVEE0YpoULX1We27fP+a6+c3kN7l1QaH979+9PVKbQ7ZV5PYD3AbgZWWf/pwDcwTl374IcPbIpiaO1cM4fBfAoAEydOpXX1tbGW6KZM4LfW14BIHwAP4shw0Zgff1BdGtvRksEgQHtVJSXozWTHUSumzAQs9aZx2uqra0NV085hgwZCuzcGTqday6dgp8td3bOqsoKNLWrA8P6Yey48cDqVd4X2qipqQF8CmcjR50FbCgoqcvKWNacIhnsi0l1TVfgVH2oNPr37w8c0G9HBABnnXUWXjuyC2hwDj8/ft0peI8dOxZYuyZUmWSMHDkS2OI0B3ep6QKcNhcmzp04AVi9IlD+/fr1w4RzRwJLnOuu+vbpAxw9oryv0mMfzaj6rCrtys2HgaWLHcfHjZf3m769e2LXqeNGaY8YMQKHcRw45g6sHJThQ4cA+3Z7Xnf+uecAK9xbRZ91xgjU7domuQNgZWWu1Su9evVCbe1lmHV8FTac2I+LLr4EeGVOsMJ7MGrkKMBwYlBeVob2ILNzBgweNhzYmq2DyqoqoNnZPz962Uj87tXt2mQOnY5GW3XF5ZcDL78kPTdw0CBgb0EB8P5bpuPeBc/lf/cfMBC1tdrtwmNFp7v9KoCFACZwzt/COf9TkYQyIKshG2H7PRzA3iLlHTmx+JhlOGokcXPCYtfSm6r2o+ZPi4MLZQN6FELsyUwOkZoyA+jcgww5onlO9wRRmEpNiWLfO9MqXL//FLYeLgw/V42T72salwUiEh+zEP2Jc3n4AS8Ta5TtPQhy53/5tao4b9J0WVBPKDWmizNU77FKY4r1DJeh2UUEAD586ZkmRYuVnl3kepzffnQaPnb5KHDudC2QvediLvDQNSfRnC66BCQdNkjn/D+dc/4Y5zy6KYk5rwEYyxgbxRirQtaM+q8EyhEJcQSYbc9wdKmKQTCzteawkbCTwD64yz5KKsfdIETlh+DlJiTLR3VPFIFQTSmmL+Lzq/c5fg/qIY9xXUwfM79ZiYLHl24cb3wvh3wi4PW+o1zsEgQ/4TL8VGcZi97X0jSOWUUZwzffeg5+/7GLHMe1AWo1D1ddWY6m1oxrA3Q7aVh9a20fJTK8Tw161mTPnXb4mLkfupjtUSe6e40TSXuKpPLLyzlvA/DfAF4AsA7AXznn0dsnioTXB6x310pf6VlbMoXddFeGfQBION5jIOwfAtlgFqWsGcT5XzYelHsMug/PcpogGFNrzbzSipIoJhymNSh+FJTbG8UVYDaCvMIIzaqdD7xSLE+oE08b2QcAcPbgHq5zqtW8foTqMsYiF1bsccw+XTtaeV15GcNHLhuJiUN7CvfrNGbqZ7P67A0Pz1VeE/ZZo+gWQ3p3kR7Pai+z5Tvd2o7+3asAyN9nlBNjL5gmK6+2lvpVmUnBOX+Ocz6Ocz6ac/6dpMsTJ2f282d+amrNbskUdtNdGfZvh59OlIIJnQupxizCggZRGMkGaC9zkyj/6WaCxdWYFc+U2UUQxKoUH8E0xzET256fNDnkQS+9XndYDcX333V+oPs+eEnW9NanW5Vr2yjVO/Izz4lDY2Z33bhyrNxUDhTqVMw+6HhcKoYJmZANZMcvq5k1tbSjT9esYCbbGL24GjM1XpPqpFdllkiTSJ7LRquX3obFb39ubstqzOIwNdpnZkmbQYJglyVlA7dfDcK5w3oqzwXpvFKNmd961lxezHfWFokp0ywN0Wyv8geKKwZeFGEpxHmOHy8pzuWzeK+2Y2qeUzG4p1xLEgalKdPHu7NraaLC3nd0/mLWuCu2CV3fkz2adXUxJlPRdAuG84b1ch0tY4VnaGxpR43GxaaYPo86LaNuTllexkhjVir8+ROXxJa238ba1JpBhnNfzrKmOEyBfpxxIy9JMOyDtaz40WrMoum8fs0UuquLqTGLxJRpWIXiQhfVwpT4AszKfMz8ZSam4VdjJvc1jNf5P44PqWo+49eUGbmPma1N6dIuV2jMdBYG3ZNF7X7Qx6drjCmMyYVqe7s+3dou3czdopiCma5adW3tb5+8FI9+aGoMJTKHBLMU4LexFjRm0Tdy+/euVFTsduydUfbR8qprcbWfblYemY+Zz/ev/WjENO5ZPkN2olhtbFqDogZDKZjFZMyU1bnfnMT37OdVcc4VH0X9fSYrDVfed4PyXFDfJp3AqNI0+3G4zpoyo23s9omuLuUhvbrkyuBHY6bxMYtQWLl+4iCM6NvVdfyVjeZhj1QPzyAXaBgr1EVTa7s2UHBanP91Y3d1RZlWY1oMSvDT2/Hwa25oas2uygxrppDhNGX68TFLi86sgGzm5jUI+tFCRuWHEGRgVmUd1+qtuGa6QU2PqoEzKo3Z5WOcrguROP+H0JgBilWZHomYhLzp2UWtYQk6+dPdpdJW+NKYlak/u/27y1fsemFfUKIazz5+xSgM7Z3zmRMu0dWV7smi6rNTzuyDxz4s1/S8vvN46PQZU08srUdoacso/T+ta4tFUI1ZGiDBzAfXnuG5UUIg/JqfWtpzgpltIIhKwnesyixJU2aWL904HsN617jORxn3KYgps6vE/8LPwNylskwrEMRlytTVi26zYC9Ma/AN4cOiGvyj8tkVzVJRfDzFJPz6mMkmAl7lCjsuBNeY2f4WnlPVb9bvN99JgsXg/F9hoDGzx0kU8+9erf4+SH3McvdHJaxYqcS3MplJNdLZFbLZv1vaMy4B9fvvLCwgKarGTJOVbl/W6CPk+YcEMx98aGI1PnrZyMjT9TspzeTMGnE0cvsgMWZg98jTLxZTznSb3gADZ2kfLyOIKfM3H52Gd1w4TCiT+f3XTRiE5rZCzKMfvHuS43xc457uAz1tZPB9C/1+RM4akF3BrDLRRTUTFpNPelXm/M2Hcbi+2XXcK42wglkcCtgoXlEZY6jbIN/OK2iZLaf1L94wzigN8ZIB3avxtVsm+s43MsEsl0yc5nzZmGc3Zba0ZVyL0vp2q8r/XUwfWN2Y9cA7z1OeS4PxhwQzn8ShivWbJudwmTKjKpVdMLnm7IH48k1mQTDT0JiBQmdUFcerrsXOrBvkgghmI/p2xadrxzjL5KPy7KapD11yJkYPcIZaiWu2p5sEhNkhwrefVq6u4g5+7PIHi2RVZrg0fvCie0sdT41ZQo6i2uCeEag14/i+V5aXYfsDN+Mz08coy28/KraJsjKGqxU7UuiI+psSZyy/c4a6V2Xax6+Dp5pd7iD2b0oawmWMG9Rda+5Ow7eMBDOfxNHo/ZoLOOdo59wR+iGqxmQfyMsYw8Qh6nARqcSjHrzDCwiCmeZ9B12V6TJp+Xh59rbCWPF8NnQrzoo52FrPq3ruqMJliOnLsvOrmXD7mEUg7MWoMbtybP/AYr7u0aJYzRyHL6WVItOs+LQfF+ve7msFAL/4gNlei1GtyrSEySi6wMh+7gUEAPDgO91x7cRgv2JAdfs3pZjhwcQ2YrmReMXnJFMmAcD/x3X7kUZwLq4iiqYx2Wc32YHGLF0r/z9/4uJIyhEUsbTLv3497n7T2fnfXoOgqNXQDXJBZ/5iCfyMy6IfTFiH8iD5iqii8JvgV5Dyao8yrVIQTFZQ+v0Aun3MwhOXxuw7bz8Xv//YRbEYxfx0G7WApH7uoPV6hmQ1oztt9ZhbxpxHzpXE/JJhokk1mgRE1PcZgBc/fzVWfMO5Wpcxhpqqctdk3e5jBrjdCezjw3FJ0NkoecgWEFlsIoVJnT4N0piVIHHY74OaOEzj7vhK0zabKGf+xb1RRdxEW4Y1YFv/9+5a5Vi+7VdjpvNZChrGy2UC8fHyxAC5bpNbsDL5zdfuw1dcjVn2/zg013YhxuX8H8EzhhHIVXjulanxmZQtjrEoZ+aTMhm69+MrkKzieNRN7upxAxxt2kRjJvvw2+vMq/qs0TUqa7OVXdiuUcYYqirKlIt6xOcqK9MLyvbx92iD208ySq6bMCj/t1imgmCWfrEn/SUscUwGkKBqebsDdFTjlMOUWebj45G7LunNdgvmCPl5L8HMT6cN6mgulsDPR8ahMWNMotmJp/5F4cv+K8w791uFlsYzjuXudV+qteXjPCfVmPlM36Xd9Hm/PE39eVXImyX3XosXPn+V8j6rqKZlFMuhm8BG8e505fLbHN86aSie+NhFzolugLcjTmRN+0XUY2ZYcz5TjOWqYooaMzF7+wrIbpqVqyZ4tXexjLKVtl7ru1KgMCPBLG5MZp1BG0K58JGOAtGUaTpoMOH/pGGKv70FM+dv+wxMpD3DA2k9XDNOPxozA9+nOHDnG03Gvv20cuXw8/H56/+71Oi6ob1rMG5Qd0c+FlH0rzC+hSq83oNKozawRxdpeAdrCzK/gomuHOIpP5pmVR3pNIV+yy7LwmhVplRzZPvtrTIDEP2qzLCoFlBZ9Sodv2wHRcHbrnn7lGZzeBP81pX9esuE7hWfk0yZnQAzjVmwtONZlel0/jdWmKVEMsvP9B0mB6ewqUPstOMH98D2B26WXtvOeSABRazVwD5mrHg+Zv1sS96/8ZaJjvdsz7OynOGOq84yTje4xsz8Hj91Yr0bl4ZQkoZvH7MQ712Zpkcifs3M4wblNqr2WTaxGLq6+eUrW/wlLs3PXBBUHcufM0xDzFfse+Vlzv07Pas+V0dpc/4vWB3k7VXWjp0+Zs707BozXfwws7Lp60o8X+lYeJAtmLdRJHnJjAQzn4SN9i0j6MzZMehG1JbsaZaXMd/pJm/KdEuI9iJ5Ov/7KH8mwwMNqmE0J6KptVirMof0Kvgj3X75KEEjWfj16dox6FZlbq4I2p/8mMOC1JCZhtDvwgXht88yyfB6/YEDxOb+Hz+4h9n1Re73uufuVePeyUAnoMq0b0bhMoRz5cJqTtM6MfVfXPutG3HfpepN5a3swvpBq8zYTDhvIVpWRG22boumoGVTX+D8ae/HnDRmHZfbLx/p63ojwSxgWZw+EdFgb8hZjZlcwBHJq7kjKkdQpLNl299hnKVFgpoyRfzIVnZTK4Pb1BzXB1LcsUDlBM2Yvzr0+xGx8opLY2YRZl9L43IYFOyGiWpTOuA9vvjVmOW1LrnfXasqMOsLV3ve5/YxiwZV6VXP/bvbp0lXQ4rXn2VbpCQTwsyc/wXh3a+bQe686eSua1UFulR4awpDa8wsU6ZrApn7X7hetKyIk6bqEDuDuMvm73q7HzbPa8y8tG7JQ4KZT87s1w3bH7gZF57R2+h6I41GwJbgcP6PysfMIZj59JmIsBxhcRTDbsr0qTHTXb7zaCNaAyzNDONjZhdIGCuexowx4IfvnoSnP3UZAGeZZfGcLFTxkCz8fkQsoc+fg7P/OhLbiewdhTZl2v5e8tVr/SWWw1NjFsVqUoMkXIGZI1qcoUpF9Vi14wdKj4v95DLbXqhekznVcfEaUQg27dd++rDJpeFXZWb/d5sy8ydc19ufVZw0RRnk2NOUqRmLMnnTsUceKfiGkWAWEPP4Xmqs5epBV9IpZI9QWFq4rFDm1MjosrAuK2LkBEU59AXwGy5Dx+JtRwMFTAwTLsM+G2WIR7Mjg4HhnVOG50MKODQHQq72Orz/bedq0w26stGXKTNApbid//2n4U7T+Zsx4Ms3jcd7xleih2Qj8bMGdMP/XDcW4wepzYmNLe3aPO3v4r1TRwAAenZRm5rzz2mfAGhzML8mCL0lZknA/8fTtR2Wzw+8LF/ZBMvPRNY660d41o7BeR+zsKZMeS5M+N9xve2g2Dfj3qXDURbht91saZWrmBupB4UEs4CYvlpd37Q0Xl5jzP+974LIyuOFNZBbXUtlslKXI9lGLxs87H/LOqV9Y+Ji7uVm4ecbM7SXM/ZUsZz/RVQmbs6dddzVy9/Mr/N/mSWYmd9jUiWiZk+MmC/7WPn9/Lk1Zgyfrh2DN4+qkr63l++qxTlDe2HmnVeiW5XcaXr/ySZtnlZ9jR7QDQ++63z85Y5LMPuuWn/lNmhUcfmWPv2py/ICpWl+sjP+BW3v55HFyXIIbh5fVz/tx5J1dMOT6pl6d5ULtyqUeWjydvqY+crOF97hMoRJot2UmfvfSzBLg9hGgllATMchXSOwznkldcGI3gbliaY55QWzXCt2CjgGg1XCLSpfp4qZrex92GeYfrZkCopYAj8fNfuG4eJqKFnakSHmoxHYRXO4jqDbGmU4x5BeakdoO15948x+XVH3pemOYzWVgk+djzKqy6H/rb7PHa/Oor65TXuvuIXVxWf1c0xEXHnl/re/FzHnK8f2l5RRXYYwdTeyfzd88JIzXcfHDuzuKx2dJlx2xsTHTCS7KrOAab/2o/31O2982+SheNvkYf5uUi58UCsSdJH/o8S3ptRWMMukKtNOO/PwX66oIcEsIKaaIV3nrMybDcO3hMg0ZoIB3umr5Z1/0m36v6/JbhB+1gC5c6/sA2ff260Yam63CcT83olDe+YFEmmA2ZhGFdGk5BR8Rc1BmfJcWKy+wjnw4uevUkYntxOkBKJgJlvIdbShxfH7/9nChPzXFaNc1+uEaK9qUmlyT5zWb3FjCSTG8Qgll4nHLjmrn+Sa6CY0m77zJuW5ijKGRfdci0kGk1U7fk3+AZRGElOmYR4+6kofL849Kb1sTH/f+6Ual9uRt/3++MZQv++t0tZxr50wEHddPw5ff8tEjzSS/oqRYBYcw3enM41Zg4VXXJV2A7tNVH3BLZiYaT9kg0LUvHbvdZ7X3HjOYGx/4Gb0VMyKZM7/dgf+oghmoknLZ52dnQthwFAc0+uP3jMJ1wurA3Xyuq9Vmb5Nmdn/MxmOHl0qMbCHt9YsSJPsIgpmBonYwwIM6ikrl3rS4/UxUOV/QrP34DfeMjHfPvy2a+7wMRMFb3daUTbDSo1PUk1VOQZ7aEplVeX3+ZV9UtMOxDhmph/4qP0lXf3R97Prj8vqxt4+H3yXe6PzN507GPe+eYKvctiZfdfV+On7L/C8Tuf8X1FWhs9eO1b5bVClkQQkmAVE9e762gJx6q4DCk6RA7qrTQsA0JYxWfkXTWsSY7yUGX48rDNxygmiCWbJvWYr2RyzOUkB2zJqU2YchNGYZe+3aQCFxF5efzBosZS848LhkgUL6utl26CoCOr8b91nojELMoMP0gzacx/YCUN64mMSjZnLlKnw0/NTnntvnoCuVeVSP6LbLx+Vfxem7dokdIRscuNalRlybeDw7vLyThjcU3pcxi3nD8n/rQsr42dVZqVuom3TmDHm/U6t8yZyWX5xle4a4VoLv873qv7ChP9VyPZg/cUHp+ATPgJPi4we0B23nD/UM3OG7D6fVkBse+QC1avzWjmeBCSYBcR0rNd9FKw2079HNZb+73W48Rx5zCK7qS1u3BHPzT8eQHHVwCbaEsDZl2UfqDabxqwYzvRikn4FB2b7I6kVRqoI6BzuWHg6/K4gswRrS8sgmhyDIC2h5kOuwpLvbzl/iEKr5JLM9GUwyP+Ksf2x9ls3YfnXb5Cez2+v47ON6d6K3NypTn9IL/Vm6SruvaQGC+6+xnX8sQ9PNU7jijH9cfGorE+m332rVY+jE3LKypzvsdg+ZqrsdMKkNB2P9G86d7CkXPGNQ/bvokkua755Ixblws84ty2UX//3XAigNEGCWUBMBRDdh9O+J1n/7tXKxm0WP8yoOHkuH9NPGpFZHHiY4m93AbzL0UOyN19YueJSib+LiJfzv91SLJrhYvFjdWnMgpkaZAFmi4WjXYgzdIePmT4dv9UrbskkmhxlBCmDW3j2LpvVn1SRzsUknHWoz0CVf+QBZqVCl/O3rA+J19j7zc8/cKGvMgBATQXLa15G9M3+/+A7z0MvgxWG9rH5t7dPMwqQq0vDjq4+ywVNsWnV++kDopeATGMshjiq9Oljpg6XkT3+8StG4aJRfR3n4hqHrho3AI+8r9B+rLLddf04eRlZ1hRumcPFLQZl9BcsVmTKLGFUL0/UAIjX2bcLyZ+zOTTLGDeoO64Y414J5chHe9ZNTWU5nvm0e6ag2yPQaEN23SWSc2E79O8+Ng0rFNoCGZ6bPhehVwbdM/GJj12UT8G6L20aMyBeHzPrca1+9tHLRnreE0SL6zY3e6fx/64ajf+ePgYfutS9ilCWJhM+oDq8zEvK+wK2D4ePmWtxh0Qw09zfp1tVPv6dzMzlRe+uVdj+wM1477QzfN/btaoCYyQrOE3NjCK6tp3dzFv4LXCfxPHcj9a4Woj8P7KffZGTHJ0wefN5Q1zHTHzMRD+tuIbNPl0rHYsXrHymCYKhCufewmaFpACzJYzpu9NdZ7qNEWMMH7tiZCTlsXPO0F748XsnO465Vy95q4Kz17mvF/nWree4joUVhKoryj1n0c5Vmfr0iuFjJmJaB1ePG5C73n5vHCXyRldkcaN1Hb59zART5pvOG4J5X56uvSdIExPbsUk911SV44s3jldu1Owyk9v/9kg/qDZdjEvohYm/VZAPlyV8JPXNi8rFQrfPoskWdjJB2e/kxD65f/CdBUd71XtRLaaoqSzHecO9t6/Kp++4RrxHUdiI8Ts+O7YtNP1m+8ohHkgwC0gUHd3uKOp9bbSannycMpdqXLMnokG6qmJMGNITI/q4nSyLMlD70PrFqYF68fNXAXA7Rgf1f2FIbnanEyqcJh0vyczfV0k0ZZoQSDBz3VM48IkrR/lP0CMPr/fopcVQEbQ9O+KYie9XkmkYwS8utH5yHu1S6a+l0ZhVlntvYu7oN7lf10yQbyNlx95N7K+0h20XB5Y/79QS+dFgZ+/xPvHlm84WThXnxf7pvy7BJ64chf7dq6Tn3W4Vds2+WR4pUJiRYBYUpSkzQBomQp7p9h5h6Vnj9AMz1wxmL6wsL8NPbpvsitZdUcakaRWjEzDF3zJUH7Lf3T4NMz53BRbdcy2+dOP4/PGvvvls6fUio/p3wzhrax2hkfgV8nWBHouF04/FWRC/Pma9FNvuyCgXNGZxwQC8/+KC6cz+HNdO0G8srkyT6X/rUGoxIp9oyIQJ5zGZAkZ8Heo9LuNvtH6zkK9ElSeiqs83nTsYjBVSUvppSY5XV5QbrS62sNehrK+JWejCj8i6kYnGTDQPF2soGj+4B+69eaKnH5yFUzAzKyXFMesE6ENMeH9g3zZ5KAC5tH/bRfYPRzSNqV83wRHSoZrXPIvt1K2Th7liDWVV+IWL3nFBNhp1MQZqh3NnQA1D7fiBOGdoLwzu1UXw64hOcxrX9XHg1AzYTnCuXQkl1i/nwNwvT8diw028LVOQ0wfK6FZfMOb0X7O3U92HTofblGlecJV8Zawx8ynI6upXPg4401f5TaWg6QLwrjfVaZUp0+5/pSOSYOK2NMod2jB32tdPGKTV8knTV+arvqew+tdXVoExLaNdW2hatDSMrx4b2REqggpCjAEDe1Tj4KnmvAlLldKrd1+DoTlnWbFDf+8d56GnD02DrBwi33jLREwc0lN5nYmPmYU4LNtnLgN6VOPMnHATlWD21klDcaYiHk3t+AHo160KRxpa8vlVljO8bfIwXHBGH1xwRm+86SfzADgFh2kj+6B2/ABXepYjMxBNJw6zKjMp7EUWhYZKx2AoaluYK2Byr5pKY62ZlVcmyO7xPtD5mFUFFMxi0ZjZ/n7TuYMxZ8NBNLX6D5g878vT0dqewa/nb3OdE2UsqSnT8HWkwbEa8P5Iq4qpcjsw9xfW32+CvfnJfK6sPH770Wno1bVSm7Ys3lyQMtrdK4qB6ZhZEeMuJHFCgllAVK9YHKBkbeGlz1+NE6db8dV/rFJeIx43ccoNgr2xvnPKcNcHz09MKh3lginTGhCi6iu6jd4ZY7jhnMF4csnOfJ31716Nh949yXWtfaD72yfl8W0G9+qCYb1rsOf46WCO0MJv31HJA5oyrQlBFOg0qZNt2+UM7e3UnFaUMdg3MvIbiFTmYxblgJtPigkmcNuPygp3fkZ+oiF6rFJQsJ34xQenoKG5Ded844X8MVPn/xF9nZMa7vjb2ydSTF+VX1LfRl07k4+t8oLqnP9VadlxBOwOWBf2d15exvCT2ybjf55a7pqwWb/99jG1Gda7TMUSftTCoxN7nENzU2bykCkzIGHaX6+ulTijX1dPzYe9Ickalak2yw/dc7HGrG1/7A1bl4WrQwoSaoWwwa/1YS1eHC6nIKia4ZuWZ0JOs2haet2SeN814DE7lYUPmfWFqzDzzquMkn/aIOCio+0J5yrKy7D9gZux/YGbXRsGy0yZfhBXZUaBrB7FY/bWK5oyxw3qjk3fVu/vaOHaK1PS1vzGK/PSwgUOXmxDrGpZmqbvIw0fPcBZT7Kiq6pNOYkS34My3/A14BDMGMuvAs7PKZj7OhVyH7PC36aTxmJrzFTfTLF+a6rsgplx4olDGrOARKqtUsxs7HnIltr72dLFlIryMvzljkvyjur2VZph8shqzNyjYbHDPQzpVYOPXjYS77tIHhPJ7wqmMgY8/pGp+PgTS7XX6SOph/942pGFDxkzsIdx+ibR9HWbmOsQTS++98rM5WUXdMM2IWmAWbG/2X6Kpswyxsy2vfH4eN//tnNx8ai+uOHhua5bdxxplCYpjguqmHK+5VjNDbKPdRpNmbr9Pj1XwSqOq8I1FBSt+nSjmIjalXZZHzPnpFMU0HTvxl6eHl0qcKqpzfEM5Yyh3UpfuPdH75mEzQfrc3kxV3pxYqoxs3+/TGP6kfN/CaPq2K4As7o0vK6xnZC1KafWIvtjeB//ARxFLj6rH/rk9hqzzzgQQhAUNWZWLYkdOe6AqYwB9731HIwfLBdUyn3GrmCMBV6lZxF4r8wAg+C6b92EIR6bQJuYPuw5mxbj/AHl+K8rnfvlBY9j5vNGn4iPZG+nVUIkdWOhxCUcOM9/6JIzCyt3BVraTfbLdRPUf9GOy/Qu9TEzXJZZBMzMyh7X+9SYiZNsU8EhCPZ2VFHGCqGPhMzz+8oq3gUHx4dtwZCtHRoc/qO2pi4+0zsuHJ4Pm5GvloiG7+6SXWLsmDbrrlX+FQtpcEUjwSwg0WjMrP9VszC9VkJmyhzc0/3R/cDF/iNmW3SRRF2W4SVQ2QUeBnUctV9/xHwvvDiQfXRkhJCNPLUcnnkL//uhpqo88KpCO0Hk5y9M6YIBwvYnvvfKzPuYqeNsRQFjalcBsf7s4VN0uEyZMazoFX97+USpcPiYCe9IGiTV9TvdqzK9UL0br3HO08csgi+uaGoUa1rUmOnoJhGAHKs+DTXjposfTJj7pen44g3yLZcsTE37TlccU41Z8pBgFhBz6VvXmJ3/6/Jw+6cIglvuf9lwqBsi7cl2lZiwnHuNKQoKiYlKct7+PNaH1WUyUqQv7mcWFK/OaaqxKwiWetOGeD2QXZV653Vj87+DDtZBBRKVGddf3sy4DOfboouH1YhazdGPxiyIOxpjzjbn9DEr/D1pRG9cN9FMY6ozjwbFKwSHXxlc1j9MVmVCMdFSXAYAuOZs78CqYdBqfj3KqXoOb1OmHmfwV+/8pGnYylBRVuaa5Hr5LnumLwh+fu4J06b7dK3E8D41GNG3BuUeDVepkRROdAniY5YCSDBLkLxdXvEW/Dn/W2rrbC/1G7vm5vOHePrJ6Dq6t8bMuV1JwZQp5KHocXO+6H8jYiFlAN5OyuVlDAN6VJtHiVYc97r/tmlmMejeeeFwd54hB5hPXn2WY+VkEBpb2gCYCT1Pf+oyrL//JgD6TeJfuPMqXDXOHZ7EjtzHLPoRl4Ghd9cqjM+ZFlUaMz85i9cGKbVrw2XhvNjuLE2135V5Wr8kzapML42z/ey7prjbtmoDeH9416yXf66yXytNmdb/0bXFz18n1xo5vwuSMgjnwkT+18UkdN5jTfSDP/87LhyO+V+5BvZAvcr8DPPpGmRVZgpsmSSYBUb+8nxF/s//7611kc2MmeRaS5PwFduWGUYaA4NrdO3Vy6lbDJeRyTv/m3UCcXWfX6wBv6VN76tTXsbw6t3XYP39+lV2XqZML8HM6R8oZ3ifGpw1oJvibPBBkDGmLZ9JezlxutU4v8rysrwTrmhaswsM4wf3wDsvHKZNK45VmTKs91Odi8hury4/e4HacfXhAK/vuc9dge0P3KxJM6TGTFKm3sJiErlWLdefJQGAlXlJjq371k3eN+b4n2vHel8UENXHOUqNmRc1VfKX5xTGmHvRWH7Cn/3/zZKNyk3LaLq9mnVLsbRSpvnUBPExC1CeqCHBLCD62YPtb4M01GpZfX5MkpHMqV43C/XzcZAJghZeGjPXrE0RLiOuTmF9YE+3tmuvKy9jqCwvczl4qzD1dfCz4tZiSK8uuOOqs6TnZHnY+fMnLlafjABVmb2+x2HDZcjjmPlLQ8TodpUWIVRG/gvepUq9l60sxbzGzGc92zWSPbpUOgWmXCb21anW1aq4adZvrzHNdOUcAHz+er0fkg6vNqM63dNjgujpY+ajsZqG9BGd/8Uc/PqUqsYmXdGjjmPmmYztfL8u6ourHT7Sphozo8tihQSzGJj/lWuMrvNesm1XWbuvlQlK+Zmr7eQXDZ2TVYwe0A1vmTRUW14vJ2O76Ywxu4+Z87q4OoXlBNrsIZipZsQqVFczZHcIeN9F2T1DXYOs7UZZlo+87wL88oNTtIOqrqSXje6vOesVvkN7K4Dgy+L91q8rX4nGzCvFYD5mOu1AUE2l/rcJlUI/8/JbM13Mkr9fcbymShJChUlMp77yi/cLaP7e3eUQ2/e8L0/H3C9Nz69W905R/mx+mr+q+C7BrJBp9r/c/353xygEplVpzDT3Rqwx89xk3nb+h7XyHV+y5bF/Q6PJuxiQYBYQZafnwLDetpAV2llG7pK834xwgf3jLXlTch8z6/rCSa+lx17MvqsWj7zvgsCrMv9yxyX40CVnOu7nCo1ZXFimtCYDU6YflNpOZH2rTMwIMi3BWyYNRT/FggddCZ/+1KWe+XlhZIaSvEsTykUfM/NbAQB9umY/jOLqTi8W3H0N/v3fVxhfz4T/ldf5aL9iW+9iEC9OxMtfyG3KVIwtHmgFd9vf1jNZ/5cr4qYVJo72svorkykm6Xq2QiGNqooynKHY8i2bp6WtsgZ177J5CQBKjVmZeJ0zzlhQweLsIT0wuGcXfPmmwkTeXGOW/b86QJvOp+/jWtNh2j622vc4jqwgMUGCWWDC+7hYavHG5jbpeXvjcwkwzDkIW3/59d3yg9bHzPXBLdTP2YN75hw6me18ljhCCMiwwn40GZgy/eC1fYkqlpBzRW00GhjAx+CjQbaE3p13NBqzi0f19XX/dRMG4kfvmYQv2JfTS4oyybYSFMhOls4TjlnIA8wKvw38QL0Qr+0q00J5YNXf2y/Q++Llr/ft+O19PXNoISzBLPtbpTGTmjJ9lay4eJmIXdcr7nOnq29H9tArqgUbavcJp1Do9YUSx6Tu1RVY9NVrHdr2Cs2+t7K8g+4j607P67xZ67EPN7dOHhpJ3sWABLOAqGYzU0b2MU6jf4/srP9wvXz/QucAKJxzXessl5dg5uUDJb1HyLWqvAyjepZ55seszdptl6gEyNhMmbmP4OmWiAUzj+PlEtMb4HzOoOp/2eAURYDeUf27ecbmCpqL3eT98l1X4xtvOcdfAiy7esvahkbF7z9e8LHz06ZcwToDpKFCTMNkhwV3GtlEHnrX+Vj9zRs9rw86QTPWsFkTkFy7y2vokowwm8PcXO+uI7+1dvV4/WpiC6/3MeXMwvdD9Q5Mdy2IYoGMM46Zd57RrKr1rn9jjVmu0Gf265qK1ZamkGAWEFWT/9n7L3T81jWFfjl/hcP1LdLz9nu9GpUVm2pQz6ywZzpx8aOtEYuw8Ttvwm1nZ59Btyqz4BjqPl+svmKZjTyd//365HhozKywJa3t/p3/gxDV4HO9R2wux7v08RG2z8DPGtDdeJFFPl/pR9R9rFdNZX6/1yDfJ2N/FB/VLb5nqd+WIRXlZUYuCqabmPvB2Xad+VQoTKfWPU5TZnYD7j9+PNqFKlH0AFc/UiS6/YGbsfqbN+LWyWYaTK+ymUysxEsKk4nc/wErQDYOmS7GsO7125+DYvrdkgWk9k47eUgwi5D+3auNzEAWF+ZmR2crtgfyo/a//fJR2P7AzehVU5m716x5TRqRNe/IYgqJyDcvzv6vM5nIzJXW1lGDhe2B4uoUeR+z1mh9zLz2NLac99sy6ny9Asye0dfp26J7t3FvaWWh3ObFY/wLW75iCfKmpqwwpvcgpky/BK1vk88Yg3s1nupDLjUXA7h18jBcMVa/UCUKTE3ThfPm+PHh9err9upT7YohTh6vGjcAQ3p1wadqRwOwPZtPfz7ZqzOdqFpZRbGrCGBQXmONWfZ/zfAryTt50Yw2MQ+IrNP4fZ8XntEH8748Xbm/ZZhB37RDDe/T1REXSYcsRUsRpFuVmR+8bSncfvkojB7QHXuOn8aCzUf0mUTABWf0BgB88BJ91Psonf+BQr20ixozh4lAn+d/PncFjje444bJbvOr8RO5503Z+Hdeqdifxk87DbsqU4bqkS88sw/W7z8l3dTdIFV94gEQJzZdK+MffgsuDmYaAyPHeds1hb6dxU//if37Z3tmlwaPyf/WHTPBuk+2NV72vN40aD9vGi6jb7cqLLznWle69tsnj+iNN3Yed9z3u9svUuadz6vMbJxqze3lKpoy320w4ZfhvRm8WTqFuHqkMesUyF6zvbHc95aJALw/uiP6qm3fslWXpoiX//T9Fzh+eznByxMt/Hn5mOws11IR6wbkvE+q7ZLyMobpZw/0PQCeM7SnvxtyDOzRBdsfuBm14/XbwPgPl6GXzCxTZltGZ8rU59GzS6VjRVjeZCFb5m/Yo1Xj1O2XjzJLICBB92608PN27nvLOXjuc1c6V0mb5iNqWLwk8ABphjFlGucZ8DOj+5DJouZbV1urZk20gelZlSk7z7S/VVRXlOPh907CU3dcYnS9iF3oUr0B03qzv8Lf3X4Rvn7LxPzvgT2qcenofkLe7jQcwZQ1eTXnLBGiKfPuN50tuzw05s7/linTT9pBShQtiQhmjLGHGGPrGWMrGWP/YIz1tp27hzG2mTG2gTHm7d2aELJxy955RRNdEMKsYBIb1y3nO1ekHDolX3CgTTP3/88/cCF+9aEpAOwaM2eG9uoRZ9V2REHJawD8zUenZa+LqfP4CXCpK0deY6YwZcq0DlEQNi2ZEC3D/uEO6mMWBNmArEqxqqIMEwVB/re3T8OsL1zleb9pKf08jXhtsfxx/ODX51Rsb1+4fhy+fstEpc+Vc0xL8Avoc3GUH95+wXAMVU0GPBz6naZM+bXWJFicbFvkV4LbMutVU+lYWOClrcunZbjLRUt7dqIvtunAGlSP28yd/7P/+xmjOnMcs5cAnMs5Px/ARgD3AABjbCKA2wCcA+AmAD9njMU/rQyA9xJ7tTBiim4/N9WMIb8s3SNn1UpQE8YM7I6uVVkzjDUT0WrMrP8llwzrXeMwpXoNiHF3Gd8aM6W2kznSE53/7fgWpjTCU1hTZtxx5UL7mIXMf/r4gRgzUO7TCdgFUyY9HgZ73X7/neeHTzAhCubR7A4TH71sJPrkzMU1VeX42BWjlO+ZO23gifHeaSN8FSOqbuHlhO7UmOnDZVj+xCL292MnyAIQ+zxKV3RrqzsxXEbgYMye57NXeI0nQTRmaSARwYxz/iLn3AretQiAZYi+FcBTnPNmzvk2AJsBXCRLI404BP4IOrJudqlK3nS1YxDzjuyj3a4QzGSrMqMkrjHdVHBgwv+q8yqtiE7o/tw1Y3yVwY5fjZ86TX06Sud/j+Hfr+D74/dOdvw2nemHRUxR+Z59ZG2/9j02wSBN+DUDnjO0F+576zmuQLNGefksm18cMqAts1e+VIthvWtw/9vOdV0nuz5KvPqnQzBTatey/7d7SBu6s6YuV/bxUCdUThySXUT2jgudPmVRhgJynneXT0YhjqS77LPvuhozPucOOp0GU2YanP8/BuAvub+HISuoWezOHXPBGLsDwB0AMGjQINTV1cVYxCz19fX5fI4eaXKdb25uzp9fcyArdzY2NjiuaW1tVZb18GFnmnNfeSXf8A42Ok1h69evQ92pzfnfVpoHD2bTWLt2neucxd0XdcHQ7upyqGhsbAQALF7yGvb2yAocjaebADAcOXzIkd7OnYUQIK+8UgfGGPbWZ5/BXk8iK5Yvlx63rj/enHEdi5JX589HdYV3zzyUe1fr1q5Fj2Mbcd+lXXDfQtv74xnU1dXhZEthQLCXt6G1cHzv7t2OtIe17kFd3T5l3gf2Z7WdW7duRR3f5TinqhPx+MmTp6XXie9KleaxY4X7d+4slGHHjp2oq9svTbu+vh5LlyzWprtunzPYcubABsfv+fMXoHuV8/2canEPun7aRuPp0/nr6+uzbXz16lWoOLgOp3L19MYbb0jTPnH8uGdeo3uV4VgzxyuvvCJNwz6ueD2Dn+eqq6vDrlMZbR4iu3dl29amzVtQ175Tes3yFSsAADyTyafZ0JCtpxVvvI5T29xGjpMnsuft4+GqlSuBfc5PUOE9mJVXpK6uDnv3Zp9h48ZNqGveDgA4fbrQXreteg3bAGzamV1Qs3fvXtTVHXGkI/qEvrrgVfSsDv/F3rZuVf7vY0eP5Z+xrS3b7pctW5o/3+90oV/t3r0bdXWHUF9fj+PHsuPMCkn9AcAx6/yKFeB7C+e3Hi/4Fbe0tLjqV1bf1nsDgM2aNgEAv7upG3B4Perq1uePmY6nALBr1y7U1R0EAKzfk303Bw4ckJarJacR6FvFUV9fD0vMF6/dcTL7zM3N7ue1qNvo/D137lxUhXS5CEtsghljbBaAwZJT93LOn81dcy+ANgB/sm6TXC8V0znnjwJ4FACmTp3Ka2trwxbZk7q6Olj5PL5lMXDksON8TU2X/PnWtQeAN5aiR/fuQP2p/DWVlZVQlfXPO5cCBw/kf0+vrc3PsHYdbQTmzsmfO/vsCaidMhyYOQMA8mk+s+8NYN9eTJw4AVi53HHOuvaT7yis4PFD9zfmAvWnMHXqVEwYkvXdWbDnJQAtGDp4EGprCz4Pi06vB7ZtyT7H9OkAgC2H6oH5r6C6utpdB7myXXDBBcCSha68resPnmoC5sxGGWPKegxEvh6v8gxeCgB/yr2rc889B7W5bZfuWzgjf76srAy1tbU4cboVePlFxzMAwMmmVmB29viIESOAHdvy5y655GKcqYng/++DK4C9uzF69FmovWp0vuxiHsrjAH68ZgFw4rgrbfFdye4FgMc2LwKOZD9mZ4wYAWzbCgAYeeaZqK2VB6etq6vDtAsvAV6ZrUz3xPI9wIrl+d+XXXoZUDc7//vKK65wrbI81tACvPyS45hn27DVTU1NTf76mtdfAerrMXnS+agdPzBfTxdccAGweGEh7dz9j33iagzvo9iqJ3fN7Hve5DpmL599XFFec24DGlracM5Q+e4Fsnxra2uxbt9JYME8dOvWHbW1V3ncCFSPOIIXHluED15/kXunhFy6kydPAl5bjLLysnwZe66cB5w6iWlTp0p3WPjJ2mw9duvWDaivBwBMmjQJV40bIH1mV514PKtFbW0tZh1fBezciXHjxqL20pEAgJrX5gC5iaWV7q5FO4C1qzFs6FDU1p7nSKe1PQO8+Hz+9+WXX6bcIs20fLdOHoopU0YBixYAAPr07YPa2mwMt4o5LwDtbbj4omnAgrkAgA+/9Vq099uGb/57LYYPH47a2nNQV1eH/v26AocP4bzzzkPt2e54gzOPrMTqw7tw6bQLMW1kYWeN3ruO5/Ourq5yfRdk9f3opkXAsWw/Hz16NGqvOsvXc1999VXurceEd2YxYsQI1NZmFygcWbYbWLUCAwc6vyt2Hu67G5ee1R/r31gEoEH6DOv2nQRenYcKzXdXVmaTb0CcxCaYcc6v051njH0EwC0AruUFPeNuAHYd/3AAe+MpYThkWl3HvmKSY34JcmucpnSZ78IFAysw5cxuuPO6cfKb7PdHUYaYDSCmPloyUyZj7mCPlQYzL3H/SNNn9LruyrH9MW/TYe016rT1BPUVCh1nLeaJrKUpcfvKyK9XCmURM7J/sK22RvXvhuF9avC/t0wwuv7S0f08w+dIVwPnfXl8OFmnwGSkIo6ice79zKruYTfFWXXdrojN9Y23nIOLz+rrEMqAYM9k769BdnMI+o4rK7zjP779gqzZdL3yioCrMlPg/J+IKZMxdhOArwC4mnPeaDv1LwB/Zoz9CMBQAGMBLEmgiJ7IGqnDJ8zQBu5MU0xP7Yc0sKd89nbndWOx/XADpp+tDwsRBvuzd61kePpTl2mvsTDbh8+sDHEN6mHimDG436EqPIQ9F3F2FlUd/OHjF2PuxkPYfUxutowMH4Oel4+Zl9O93MfM+fsGj10LdFjxmCo9VkwO7tkFZw9RLyJIC10qyzH/K9fEno+l2Y9iG6CwGH9YdSFBXO0w+gHHcpgH7AukvPP5wg3jsPVwAy5S7DNbU1WeF1pMmDikJ9buOyk9Z+LzpiPoYiRrb+Nmj4DgnvnnunGpTRiS8jH7KYBqAC/lGuIizvknOedrGGN/BbAWWRPnZzjnAQJuxY/1nu+/9RxcOXYAHnphAz559WjXdWGdsS2sDjuwRzV+8O5JuHKsfG+20QO649+fdTs0RoFqQ26/6Bq+7NSYgd2N7o2CMAMws6nMrGRUGjN7PmJQxqBFuPfNbq1I3lQk4PUKveohsPO/z8jgYilMqubRD08NnEdbznfFimCuqoZFXw3mDtARkArHuf9VmokPXXIm3th5HGf264aNB+pz96TgCwj984RlcM8u2H+y4Htqf+YWicrLtXewJM1zhvbCnC/WRlRC4Kn/dwkOnpSv0ndqzPzjazGIfUzMmT+b28wEs3//9xVYtuOoMk0/36w0tMpEBDPOuXLZGef8OwC+U8TihKK6ohwj+3fDzz4g7JGZe7tRBTq3ZhDnDO2p/NjGjcyUqUQa580f2x+4GQdPNjm2uSqYEKPtPne/6Wx17CEtbvO1/W9lOA3b327BzEurJD/+CVP/jwgIukm178j/BpdH2RYs04lboE7DcJ0OrJpwrry2/pK3i3dcOBzvuHA47n56ZSGdmKs0zATSpakNmM6/P3sFHp61EX9evBNcSFemDbI0THFsrabaraNnl0r07CIPvWEXrIJoQ4O+47zGrM1ML3Pe8F5S30bdqsw0k4ZVmSWJV1iKfJwVxjBmYHe0tGWw82ij/GID+nWvxpOfuATnDgsW+T4K8oJZwI+ySSd1m2wVgXojHrdk2k4zCnUhM2Wb4BLMDO+Lc083Xz5mNq6boDcj+jYVi2FiYv6aW/HmRB+zYtMn0DZSxcF6h7Ig0v58eaJj5p1X2vbtNLtHV9So2tmAHtW4eFRf/HmxezWjQ2PGrHyz/xdpy1tP7N0giGzjpx6vt7kgdPGpMVNRHqRdpsCWSYJZQCzhRKmqzXcwhllfuBpH6psx5duzQuUpbqFRbPrnViUF3ajWTLPhzwcprXiV0v4YgX3M/BUpUrjk73vedDYuOKOP9j7/AXydixikd0dYEW25j6Vfk2uUzPliLXorgoemAdn+g1abzSQkmZ09OPiEtVgmVc65U2Mm0QZZdRt3oGdTwm6hZspX33y2Y7FCdWU0Pmb5dllie2WSYBYQ6z2r2m3BlGX9n4bXHY6H3zMZz63elw+V4RddFdz/tnPRN7fPnlFagUoQL8zm/i+Wb2CPasm1WaxBSHZORr7thagEP4KjvBAB7oH/fsCQXcQw8u4ZxnmYUFnOpLsxtGZ4/ryT4plCRgVcgWnxf++7AGMGdPe+0CefvHo0th6qz2sh7AFOP37FKLy2/RjGDjJfEJEWHzMTC0CYdudYxGV7Zp3QEYcpM0iKdh/pYpoDrclqk6EpU0VhEmF+Txo+1SSYBcR6z6qZjdUZrQ6W1Lt+66Sh3hcZ0qdbFT5w8ZlG12rNBJJjH7okm+7rO49p001BnwGg6LwyJzMAL37+KvTr5hQ6nRozf87/1gAZx+AdhDhLISpgZB/zIAPpdRMG4fnV2UC49izahXAZ6ahhf0TZ5+1YG1Kv3nMCgPPd3HTuEM8wGyLx+5jpv8aWABx0oukX0cdM5vxvaRzDbq0mo19384mvhemWTFFTHdWqzEBhXJLv9SSYxYT1apNUSfsdKNOAuX9VrMXwRL6JfQG7qDXOQ4sgbttkqqyK18fMQ2tnE2fiHK/jmqU//N7JeNeUw/j4E0sdx9vzGrPwJpwPXHyGcj/DUiaqMS2u1ls7fgB+v3CHp1n9yrED8NznrsQEg7AnYbR7jvmaXTCT+E91r67A2YN7GMWF9MvwPl3x509cjPc/ttj74hxlIVdlBqXap/O/isIm5qUFCWZByZuT5B3WktD9hMsosYUjWmQf1CjG87xpOMW6jME9u+D9PsZVVxvyeLSMoDHrUV2BU81tulsip1httV3IKKrQBl0qy3GWxtznFcfMhO+8/Tzvi0qQqNyOogolJHLN2YOw/v6b3BHnJUwcWtzFVA5TpkQwK2MMM+8s7NBw6+Rh+OfyvZGtuPZrJrdr7oqqMcu9u7CTABZAY5YGSDALiJfzfxR+QFEz+66rPTe+jZqzBhQGArMAs2YVlrTGTBfodM4Xa7H41XnG97sCC3uIGtYrtAbNl79Yi0On5HGIVHjHMfOVXPaeCIRlMYUiN9c8oo9ZiY3rsRKVmS1Oa4KJUOaLKIoqRP63j8Wq5Pt0q8I/P3N5BJnniuCzHYeN/B+U7tUVuOv6cbjxXNmujuaUB/AxSwMkmAXES/CyOl1aVtcA2eCzxea2aYUdtkzMUp5O6SnWlFllM3Imhloy82oy1uzPum5Aj2oM6BFgH78QOFZlxjjqmWyNFNakK7u7sswKMJve9pYUUWm60jRpjRNxdxCLL1wfvbnSFNNm7XT+j6kwCj577djQaZRqGyPBLCBefj55UyYN7C6i+NiluVb9DmCiIOf5bJbGLMSo87HLR+J/nlqe//3LD16IPceb1DeIRYh5lJ4+fgDuuGq0S+AslmAel5nt/lvPwXnDe8eSdrGISmMWxeKVsQO7Y9KI3uELUwQ4CuEyhvWuweciEDzixmHKjDGfuIaTUp1YkWAWEtV7z6TQlFlMgnY0z35k+ZilsMMVAvCaXwsA4j69Xs8m+pgF4dbJw3Dr5GH5MBSXj+mPHrbo30lVrxXL6BNXnWUcty/Ooo4d2B3LdhxDz4ic+D906chI0kmSqFYDRzFpfekLV0dQEm9ChcuwNOk8+0vGXTeMxzf+tQZdqyM2wYbE8a5LzR6I0v3+kmAWEC+NGGnMsvjVcJhen8Za/fkHLsQv6ragq4F/i738HMA/P3M53vazBQC8B5OCGT26Wuha5W8oiGuIHtyri3Y1cdzd6elPXYpFWwt77t331nPwlklDPVfWdiaiM2WmsRfHS2FbO2cP+shlI/GRy0bGnr/fflsWg8aMseLJeGkJKeQXEswC0pSLr1Kj+AhHodUoZUpvbhWe2vEDUTt+oO/7Mpxj8ojeqChjaMtw41AVUX7YxHYadBPzuJGVKsrv+5Qz+2LKmYUI5F0qy3H5mP7RZdABiGpIK1JQeQdDeym2ePMgqiaWlq+BaTnsLp5RrWwsY8y12jouSlX4T3ZDuBKmqTUbX0Wlerac/6120aNLBXrVVOK+t5xTlPKlBeZTE27cj1LS34KOL+U6p1pP538rjWB5+0H1PmSPXYwxMA4TdmecRIQhMh+zIn40rZx+e/tFRcszn7fd+d/aVLvopQhGuU16jkqWKubQ7aeJ/fKDF3ru9VssSGMWkNMtOcGsSi6YieamivIyrPjGDUUpW4emVEY0DxhjuGHiILy49gDEhzKN/B/nbJAJ/0fJbz86DT1rgg09Uo1ZWqT0TkJkpswErAlBu0wUEwLOUzOfNB5GHZuYR5R3dtwqzkDuR/i/6dwhuOncITGWxhwSzALS2JIN6NlN4ZvT2U2ZcZOWWg0zXluClTgT9UoySh+zP378Yuw9flp5XvlBshXa70x6+tn+zb2F8gS+VZ1m9El2aEohjlmasD9lwccskaL4JpYAs7kkf/DuSXhs7lZsOHAqooTdlGobI1NmQPI+ZgqNmWjKNKNEeqsBca3KtPyr0rIqM8xgZT2Caz9Iw1WZUfjoXDG2P95jizUnlk1dhvB5R0Uxm8I1IYTKjkJUmq5imjItkhw1OLz9R4uFaSnefH5BgxRVgFkr7/OG9cLV4wdEkqYyr3RUt29IMAuItQGtlykzicEnDVhbnYwe6C+orafje65eO0K15jVmPuOYZfJ1EH8lpK2akxTIV913A371oSmJ5Z8WorIClFIfDlNUp49Z9v9iRtEPw9mDe+IrN2U3r4+qyNa4V6o+qcWABLOQdKnQr8osVVVqWN554TC8+PmrMD3AKkUdpTGcGaIwaxhH/o+hSPkyQD94Wh+W77/r/BhLkS56dKmMZHPzUieMXGbFqQOScfNIy3BcKqZMwF98Rj/pAfEHqi5VaJQJyLU5k4ZKrd8eobmpFGGMKWM/6QZH04Ez6fE1yn0h/e6VaRGr8z/Tl8UaTycMLu4m0ETyhGl375wyPJJ0ik0UReU8ecEwiCCUH6ciDJdhTxdIvl7SBjn/B+TnH7wQjc3tyvOFyP/xtrh///cV6BVRVPJioevfpisSkyYKU0R+6bzwTKYas6J82DyySMOAmoYydCYii/yfyKQ1icZSyDMt4TL8mPiiXrBA3dUbEswCUl1RjmqFGRMAzh/WCwBw1bh4nRvPG94r1vSTQjVu9O5ahSvG9MenakcXt0AxUBZwwLO2cIpTIDFdGUp0PjrjqswoNOQcpSmU5LeUii7B7H9FrIxBPau9L0oRJJjFxKQRvbHmmzeiWzVVsR+8BsDyMoY//tfFRSqNmihNmWJEbfOVqaGL4IkqC674OwnSstKts1DSqzITaCp2jVPS4TIqcmrKPt3MrSxByvzNt56Dw/XN0nMFgbw4L+Pvn7wUZ/TrWpS8ooKkhhgJKpQ99K7zcclZZhs4dzRKaBIdmoIpUzjuMWAVxUxuOKuVRTUvNp2pzXQkktCY+cnxc9eOxf/N3hRx/sk21sG9uuC7bz8P104wX5RVML+aS2a6fT+L/dqn2haclAqd1DU9nVgf6N5dqzCib2lJ+CYM6tkFo/p3w7ffdm7SRUkFQ3L79vX06SPIi7Aq00L1IRk9oBsAoLtt8pEW/z+iNEj7wqgvXD8u/3dUwkQhneT6yvsvPgODeprvGVpw/o8m/7y+jCZUSkhjRhSNqooyzPlirfaaztRX77xuHMYP7oHrcrPXrlXlONnU5nlfXmMWY7gBr3AZD77zfLxn6gic2a9bbGUwpTO1mY6EXWP25Ccu6bCCPVP8XSoUTJnxrcoknJBgRqSKzjSLqqoow62Th+V/P/PpyzFn/UFUVehVCYW9MmMtHgD14NmtusK1sCUNwRy/dstE42ut1cxXjO0fV3EIDfbVnZeO7gyuG4XNMktJBlWF9QmcnmSYKKX6KAYkmKWQ5D9vydMZ62DMwO4YY7BTQjEi/+fjmKVA2PLCXsaPXzHK+L6+3aow78vTMbiXuVmHiI4SaFqRYPcljXyFYxFQ+cKGTY8xVhLjSxKk3MpPdD5Ko6PedlF2f8lJI3oXPe/i+ph5U8qz3RF9u1I0/4Qope3qwhS11AOpWopNcfV4UEqwCooOacyIVFEqA1ft+IHY/sDNieRtDY+xasyKdE8UlEiTIQSS2JIpCayFXBeN6ht5FP1icPaQ7O4eU87sE0l6hV1FCBUkmBGphFTcajJF8DFjNHoSMdNZ+vj4wT0w78vTMbxPDY41tiZdHN9MG9kXC++5BkN61USSXjE3MS9VSDAjUgX1VW+syXYxYiKZ5GAtVqgopzhmnYlLO1GsxbB9TQx/VDr6sixRCWUAjfEmkGCWIkqts8ZBZ5lFhyEvmBVhSyaT9/HZa8aAc473ThsRX4GIVLH+/ptQUUKmyLSMK+koRbLknf+pNpSQYEakEuqyaoq5iblJFt2qK3DPmyfEXhYVafnodia6VKr3Ce6IRN3ESsjFLHKou3pDy5GIVEF91hueDzAbYx65/+l9EER0kFBiC1hLNiIlJJgRqYIGLm/OzG3I260qPoV3PiQHvRCCiHyCUkqrMqOmLOK4aB0RMmUSqYTkATU/fM8kLNl2NNb9VGnMJIjoKcUAs1FjDe1RxUXriJDGLIV0ZqGEHEK96dGlEtdOGBRrHoWVnwRBRAZ1qILGLOFypBkSzIhU0ZmF0jRh+X/Q+yCIGEz6nVkqiXhT9I4ICWZEKiHNWcLkx0x6DwQRFTTRsW2KTnKZEhLMUgTNIIi0QR8SgojB+T/i9EoJMmV6Q87/RKogQSAd0KBJxMULd16FXUcbky5GItDwVhjjyflfDQlmRDqhESxRrA2mB/WsTrgkREdj/OAeGD+4R9LF8EX0AWY7r1CSX5nKO3c96CDBjEgVFDcrHfTvXo0fvHsSrhrbP+miEESHwRrfykpoO6uoyQeY5e5jRBYSzIhUQf0zPbxryvCki0AQkZK0fqZbVTk+e80Y3Hz+kIRLkhyWcGo3ZZLizAkJZimEZg8koBEEkR6i0uQzxnDXDeMjSatUsSsLyUIih1ZlEqmC+ilBEETH5dO1YwAAZ/SLb+eSUoc0ZkSqoPhlBEEQHZebzx+Cm8+/GQDQq6YSANC9C4kidhLVmDHGvsgY44yx/rZj9zDGNjPGNjDGbkyyfElB9nbSnBEEQXR0PnHlWfjWrefgtmlnJF2UVJGYmMoYGwHgegA7bccmArgNwDkAhgKYxRgbxzlvT6aUxeW77zgPP5m1CVeNG5B0URKDBDKCIKKGhpV0UlVRhg9fOjLpYqSOJDVmDwP4MpwLZW4F8BTnvJlzvg3AZgAXJVG4JBjSqwYPvPN8VJZ3Xtc/GkCJoPzXFaOSLgJBEERoEtGYMcbeCmAP53yFsCpjGIBFtt+7c8dkadwB4A4AGDRoEOrq6uIprI36+vqi5FNKRF0nx5syAIBMe6ak65raipso6kR1/+9u6gbgIOrqDoZKPwmorbiJuk4aG7M7DSxZvAS7uvuf+Kbl/VBbcdMR6yQ2wYwxNgvAYMmpewF8FcANstskx6QeV5zzRwE8CgBTp07ltbW1wQrqg7q6OhQjn1Ii6jo5eKoJqJuNsvKykq5raituwtTJJxrWYta6gx2yTqmtuIm6TmqW1gGNDbjo4oswekB38xtnzgCA1LwfaituOmKdxCaYcc6vkx1njJ0HYBQAS1s2HMDrjLGLkNWQjbBdPhzA3rjKSKQPWpVJyLj35om49+aJSReDIAgidoruzMQ5X8U5H8g5H8k5H4msMHYh53w/gH8BuI0xVs0YGwVgLIAlxS4jkTwkoBEEQRCdkVQFD+Gcr2GM/RXAWgBtAD7TWVZkElloVSZBEATRmUlcMMtpzey/vwPgO8mUhkgakssIgogaGleIUqLzxmUgUg1pzgiCIIjOCAlmRKqgTW0Jgoiai0b1BQD0oK1/iBKAWimRKkgsIwgiar5167n4+BWjMLBHl6SLQhCekMaMSCUkoBEEERVVFWUYO6iH7/suGtk3htIQhB7SmBGpgiyZBEGkhd99bBoOnWpOuhhEJ4MEMyJVUPwygiDSQteqCpzZjz6TRHEhUyaRSmgRAEEQBNEZIcGMSBckjxEEQRCdGBLMiFRBijKCIAiiM0OCGZFKSD4jCIIgOiMkmBEEQRAEQaQEEswIgiAIgiBSAglmRKrgPOkSEARBEERykGBGpBNyMiMIgiA6ISSYEQRBEARBpAQSzIh0QaZMgiAIohNDghmRSsiSSRAEQXRGSDAjUklZGYlmBEEQROeDdmclUkXPmgp8unY0bp08LOmiEARBEETRIcGMSBWMMXz5prOTLgZBEARBJAKZMgmCIAiCIFICCWYEQRAEQRApgQQzgiAIgiCIlECCGUEQBEEQREogwYwgCIIgCCIlkGBGEARBEASREkgwIwiCIAiCSAkkmBEEQRAEQaQEEswIgiAIgiBSAglmBEEQBEEQKYEEM4IgCIIgiJRAghlBEARBEERKIMGMIAiCIAgiJTDOedJlCA1j7BCAHUXIqj+Aw0XIp5SgOpFD9eKG6kQO1YsbqhM5VC9uSrVOzuScD5Cd6BCCWbFgjC3lnE9NuhxpgupEDtWLG6oTOVQvbqhO5FC9uOmIdUKmTIIgCIIgiJRAghlBEARBEERKIMHMH48mXYAUQnUih+rFDdWJHKoXN1Qncqhe3HS4OiEfM4IgCIIgiJRAGjOCIAiCIIiUQIKZAYyxmxhjGxhjmxljdyddnmLBGBvBGJvDGFvHGFvDGPuf3PG+jLGXGGObcv/3sd1zT66eNjDGbkyu9PHDGCtnjL3BGPtP7nenrhfGWG/G2N8ZY+tzbebSzl4nAMAY+3yu/6xmjD3JGOvSGeuFMfYbxthBxthq2zHf9cAYm8IYW5U793+MMVbsZ4kKRZ08lOtDKxlj/2CM9bad65R1Yjv3RcYYZ4z1tx3reHXCOad/mn8AygFsAXAWgCoAKwBMTLpcRXr2IQAuzP3dA8BGABMBfB/A3bnjdwN4MPf3xFz9VAMYlau38qSfI8b6+QKAPwP4T+53p64XAE8A+K/c31UAelOdYBiAbQBqcr//CuCjnbFeAFwF4EIAq23HfNcDgCUALgXAADwP4E1JP1vEdXIDgIrc3w9SneSPjwDwArIxS/t35DohjZk3FwHYzDnfyjlvAfAUgFsTLlNR4Jzv45y/nvv7FIB1yH5obkX2I4zc/2/L/X0rgKc4582c820ANiNbfx0OxthwADcD+LXtcKetF8ZYT2QH1McBgHPewjk/jk5cJzYqANQwxioAdAWwF52wXjjncwEcFQ77qgfG2BAAPTnnC3n26/t72z0lh6xOOOcvcs7bcj8XARie+7vT1kmOhwF8GYDdMb5D1gkJZt4MA7DL9nt37lingjE2EsAFABYDGMQ53wdkhTcAA3OXdaa6+jGyg0TGdqwz18tZAA4B+G3OvPtrxlg3dO46Aed8D4AfANgJYB+AE5zzF9HJ68WG33oYlvtbPN5R+Riy2h6gE9cJY+ytAPZwzlcIpzpknZBg5o3MLt2plrIyxroDeBrAnZzzk7pLJcc6XF0xxm4BcJBzvsz0FsmxjlYvFciaH37BOb8AQAOypikVnaFOkPOZuhVZM8tQAN0YYx/U3SI51uHqxQBVPXSa+mGM3QugDcCfrEOSyzp8nTDGugK4F8DXZaclx0q+Tkgw82Y3srZti+HImiI6BYyxSmSFsj9xzp/JHT6QUxUj9//B3PHOUleXA3grY2w7sqbtaxhjf0TnrpfdAHZzzhfnfv8dWUGtM9cJAFwHYBvn/BDnvBXAMwAuA9WLhd962I2Cac9+vEPBGPsIgFsAfCBnigM6b52MRnZisyI35g4H8DpjbDA6aJ2QYObNawDGMsZGMcaqANwG4F8Jl6ko5FaxPA5gHef8R7ZT/wLwkdzfHwHwrO34bYyxasbYKABjkXXA7FBwzu/hnA/nnI9Etj28zDn/IDpxvXDO9wPYxRgbnzt0LYC16MR1kmMngEsYY11z/elaZH01O3u9WPiqh5y58xRj7JJcfX7Ydk+HgDF2E4CvAHgr57zRdqpT1gnnfBXnfCDnfGRuzN2N7KK0/eiodZL06oNS+AfgzciuSNwC4N6ky1PE574CWfXvSgDLc//eDKAfgNkANuX+72u7595cPW1ACa2CCVFHtSisyuzU9QJgMoClufbyTwB9Onud5J7zmwDWA1gN4A/IriDrdPUC4Elk/exakf24fjxIPQCYmqvLLQB+ilyg9FL8p6iTzcj6TVlj7i87e50I57cjtyqzo9YJRf4nCIIgCIJICWTKJAiCIAiCSAkkmBEEQRAEQaQEEswIgiAIgiBSAglmBEEQBEEQKYEEM4IgCIIgiJRAghlBEJ0Gxlg/xtjy3L/9jLE9ub/rGWM/T7p8BEEQFC6DIIhOCWPsPgD1nPMfJF0WgiAIC9KYEQTR6WGM1TLG/pP7+z7G2BOMsRcZY9sZY+9gjH2fMbaKMTYzt00ZGGNTGGOvMMaWMcZesLYWIgiCCAMJZgRBEG5GA7gZ2Q3I/whgDuf8PACnAdycE84eAfAuzvkUAL8B8J2kCksQRMehIukCEARBpJDnOeetjLFVAMoBzMwdXwVgJIDxAM4F8FJ2Kz6UI7uNDEEQRChIMCMIgnDTDACc8wxjrJUXnHEzyI6bDMAazvmlSRWQIIiOCZkyCYIg/LMBwADG2KUAwBirZIydk3CZCILoAJBgRhAE4RPOeQuAdwF4kDG2AsByAJclWiiCIDoEFC6DIAiCIAgiJZDGjCAIgiAIIiWQYEYQBEEQBJESSDAjCIIgCIJICSSYEQRBEARBpAQSzAiCIAiCIFICCWYEQRAEQRApgQQzgiAIgiCIlECCGUEQBEEQREr4/72OVjSOK7gQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#设置噪声幅值\n",
    "noise_level=15\n",
    "#生成噪声序列\n",
    "noise=white_noise(time,noise_level,seed=42)\n",
    "#绘制序列\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(time,noise)\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#基础序列+上升趋势+季节性\n",
    "slope=0.05\n",
    "baseline=10\n",
    "series=baseline+trend(time,slope)+seasonality(time,period=365,amplitude=amplitude)\n",
    "#绘制序列\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(time,series)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#基础序列+上升趋势+季节性+白噪声\n",
    "series+=noise\n",
    "#绘制序列\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(time,series)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#制定比例，划分训练集和测试集\n",
    "def train_test_split(series,split_prop):\n",
    "    train=series[:int(split_prop*int(series.size))]\n",
    "    test=series[int(split_prop*int(series.size)):]\n",
    "    return train,test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def data_process(train,test,window_size):\n",
    "    #将数据转为tensor并进行滑窗，得到短序列\n",
    "    train_tensor=torch.from_numpy(train)\n",
    "    train_window_split=train_tensor.unfold(0,window_size,1)\n",
    "    train_set=train_window_split.numpy()\n",
    "    \n",
    "    test_tensor=torch.from_numpy(test)\n",
    "    test_window_split=test_tensor.unfold(0,window_size,1)\n",
    "    test_set=test_window_split.numpy()\n",
    "    \n",
    "    #将训练集短序列打乱\n",
    "    train_temp1=train_set.tolist()\n",
    "    random.shuffle(train_temp1)\n",
    "    train_temp2=np.array(train_temp1)\n",
    "    \n",
    "    test_temp1 = test_set.tolist()\n",
    "    random.shuffle(test_temp1)\n",
    "    test_temp2 = np.array(test_temp1)\n",
    "    \n",
    "    #将短序列划分为feature label\n",
    "    train_feature_array=train_temp2[:,:window_size-1]\n",
    "    train_label_array=train_temp2[:,window_size-1:]\n",
    "    test_feature_array=test_temp2[:,:window_size-1]\n",
    "    test_label_array=test_temp2[:,window_size-1:]\n",
    "    \n",
    "    #将ndarray转为tensor\n",
    "    train_feature=torch.from_numpy(train_feature_array)\n",
    "    train_label_temp=torch.from_numpy(train_label_array)\n",
    "    test_feature=torch.from_numpy(test_feature_array)\n",
    "    test_label_temp=torch.from_numpy(test_label_array)\n",
    "    \n",
    "    #将label张量降维\n",
    "    train_label=train_label_temp.squeeze()\n",
    "    test_label=test_label_temp.squeeze()\n",
    "    \n",
    "    return train_feature,train_label,test_feature,test_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据划分为指定大小的batch\n",
    "def data_iter(batch_size,features,labels):\n",
    "    num_examples=len(features)\n",
    "    indices=list(range(num_examples))\n",
    "    for i in range(0,num_examples,batch_size):\n",
    "        #最后一次可能不足一个batch\n",
    "        j=torch.LongTensor(indices[i:min(i+batch_size,num_examples)])\n",
    "        yield features.index_select(0,j),labels.index_select(0,j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1017, 5])\n",
      "torch.Size([1017])\n",
      "torch.Size([434, 5])\n",
      "torch.Size([434])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "torch.Size([434])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "split_prop=0.7\n",
    "train,test=train_test_split(series,split_prop)\n",
    "window_size=6\n",
    "train_feature,train_label,test_feature,test_label=data_process(train,test,window_size)\n",
    "print(train_feature.shape)\n",
    "print(train_label.shape)\n",
    "print(test_feature.shape)\n",
    "print(test_label.shape)\n",
    "\n",
    "torch.Size([1017,5])\n",
    "torch.Size([1017])\n",
    "torch.Size([434,5])\n",
    "torch.Size([434])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#生成序列并绘制图像\n",
    "time=np.arange(4*365+1)\n",
    "baseline=10\n",
    "slope=0.05\n",
    "amplitude=40\n",
    "noise_level=1\n",
    "series=baseline+trend(time,slope)+seasonality(time,period=365,amplitude=amplitude)+white_noise(time,noise_level,seed=42)\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(time,series)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1017, 5])\n",
      "torch.Size([1017])\n",
      "torch.Size([434, 5])\n",
      "torch.Size([434])\n"
     ]
    }
   ],
   "source": [
    "split_prop=0.7\n",
    "train,test=train_test_split(series,split_prop)\n",
    "window_size=6\n",
    "train_feature,train_label,test_feature,test_label=data_process(train,test,window_size)\n",
    "print(train_feature.shape)\n",
    "print(train_label.shape)\n",
    "print(test_feature.shape)\n",
    "print(test_label.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#实现FlattenLayer层\n",
    "class FlattenLayer(torch.nn.Module):\n",
    "    def __init__(self):\n",
    "        super(FlattenLayer,self).__init__()\n",
    "    def forward(self,x):\n",
    "        return x.view(x.shape[0],-1)\n",
    "#定义模型输入、输出、隐藏层参数\n",
    "num_inputs,num_outputs,num_hiddens=5,1,3\n",
    "\n",
    "#定义模型\n",
    "net=nn.Sequential(\n",
    "    FlattenLayer(),\n",
    "    nn.Linear(num_inputs,num_hiddens),\n",
    "    nn.ReLU(),\n",
    "    nn.Linear(num_hiddens,num_outputs),\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#损失函数\n",
    "def squared_loss(y_hat,y):\n",
    "    return(y_hat-y.view(y_hat.size()))**2/(y.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#参数初始化\n",
    "for params in net.parameters():\n",
    "    torch.nn.init.normal_(params,mean=0,std=0.01)\n",
    "    \n",
    "lr=0.01 #学习率\n",
    "num_epochs=200 #batch_size大小\n",
    "loss=squared_loss #损失函数\n",
    "optimizer=torch.optim.Adam(net.parameters(),lr) #设置优化器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 1,train loss 0.011774,test loss 0.038488\n",
      "epoch 2,train loss 0.011774,test loss 0.038487\n",
      "epoch 3,train loss 0.011774,test loss 0.038487\n",
      "epoch 4,train loss 0.011773,test loss 0.038486\n",
      "epoch 5,train loss 0.011773,test loss 0.038485\n",
      "epoch 6,train loss 0.011773,test loss 0.038484\n",
      "epoch 7,train loss 0.011772,test loss 0.038484\n",
      "epoch 8,train loss 0.011772,test loss 0.038483\n",
      "epoch 9,train loss 0.011772,test loss 0.038482\n",
      "epoch 10,train loss 0.011771,test loss 0.038481\n",
      "epoch 11,train loss 0.011771,test loss 0.038481\n",
      "epoch 12,train loss 0.011771,test loss 0.038480\n",
      "epoch 13,train loss 0.011770,test loss 0.038479\n",
      "epoch 14,train loss 0.011770,test loss 0.038479\n",
      "epoch 15,train loss 0.011770,test loss 0.038478\n",
      "epoch 16,train loss 0.011769,test loss 0.038477\n",
      "epoch 17,train loss 0.011769,test loss 0.038477\n",
      "epoch 18,train loss 0.011769,test loss 0.038476\n",
      "epoch 19,train loss 0.011768,test loss 0.038476\n",
      "epoch 20,train loss 0.011768,test loss 0.038475\n",
      "epoch 21,train loss 0.011768,test loss 0.038474\n",
      "epoch 22,train loss 0.011767,test loss 0.038474\n",
      "epoch 23,train loss 0.011767,test loss 0.038473\n",
      "epoch 24,train loss 0.011767,test loss 0.038473\n",
      "epoch 25,train loss 0.011766,test loss 0.038472\n",
      "epoch 26,train loss 0.011766,test loss 0.038472\n",
      "epoch 27,train loss 0.011766,test loss 0.038471\n",
      "epoch 28,train loss 0.011765,test loss 0.038471\n",
      "epoch 29,train loss 0.011765,test loss 0.038470\n",
      "epoch 30,train loss 0.011765,test loss 0.038470\n",
      "epoch 31,train loss 0.011765,test loss 0.038469\n",
      "epoch 32,train loss 0.011764,test loss 0.038469\n",
      "epoch 33,train loss 0.011764,test loss 0.038468\n",
      "epoch 34,train loss 0.011764,test loss 0.038468\n",
      "epoch 35,train loss 0.011763,test loss 0.038468\n",
      "epoch 36,train loss 0.011763,test loss 0.038467\n",
      "epoch 37,train loss 0.011763,test loss 0.038467\n",
      "epoch 38,train loss 0.011763,test loss 0.038466\n",
      "epoch 39,train loss 0.011762,test loss 0.038466\n",
      "epoch 40,train loss 0.011762,test loss 0.038466\n",
      "epoch 41,train loss 0.011762,test loss 0.038465\n",
      "epoch 42,train loss 0.011761,test loss 0.038465\n",
      "epoch 43,train loss 0.011761,test loss 0.038464\n",
      "epoch 44,train loss 0.011761,test loss 0.038464\n",
      "epoch 45,train loss 0.011761,test loss 0.038464\n",
      "epoch 46,train loss 0.011760,test loss 0.038463\n",
      "epoch 47,train loss 0.011760,test loss 0.038463\n",
      "epoch 48,train loss 0.011760,test loss 0.038463\n",
      "epoch 49,train loss 0.011760,test loss 0.038462\n",
      "epoch 50,train loss 0.011759,test loss 0.038462\n",
      "epoch 51,train loss 0.011759,test loss 0.038462\n",
      "epoch 52,train loss 0.011759,test loss 0.038461\n",
      "epoch 53,train loss 0.011759,test loss 0.038461\n",
      "epoch 54,train loss 0.011758,test loss 0.038461\n",
      "epoch 55,train loss 0.011758,test loss 0.038461\n",
      "epoch 56,train loss 0.011758,test loss 0.038460\n",
      "epoch 57,train loss 0.011758,test loss 0.038460\n",
      "epoch 58,train loss 0.011757,test loss 0.038460\n",
      "epoch 59,train loss 0.011757,test loss 0.038460\n",
      "epoch 60,train loss 0.011757,test loss 0.038459\n",
      "epoch 61,train loss 0.011757,test loss 0.038459\n",
      "epoch 62,train loss 0.011757,test loss 0.038459\n",
      "epoch 63,train loss 0.011756,test loss 0.038459\n",
      "epoch 64,train loss 0.011756,test loss 0.038458\n",
      "epoch 65,train loss 0.011756,test loss 0.038458\n",
      "epoch 66,train loss 0.011756,test loss 0.038458\n",
      "epoch 67,train loss 0.011755,test loss 0.038458\n",
      "epoch 68,train loss 0.011755,test loss 0.038457\n",
      "epoch 69,train loss 0.011755,test loss 0.038457\n",
      "epoch 70,train loss 0.011755,test loss 0.038457\n",
      "epoch 71,train loss 0.011755,test loss 0.038457\n",
      "epoch 72,train loss 0.011754,test loss 0.038457\n",
      "epoch 73,train loss 0.011754,test loss 0.038457\n",
      "epoch 74,train loss 0.011754,test loss 0.038456\n",
      "epoch 75,train loss 0.011754,test loss 0.038456\n",
      "epoch 76,train loss 0.011753,test loss 0.038456\n",
      "epoch 77,train loss 0.011753,test loss 0.038456\n",
      "epoch 78,train loss 0.011753,test loss 0.038456\n",
      "epoch 79,train loss 0.011753,test loss 0.038456\n",
      "epoch 80,train loss 0.011753,test loss 0.038455\n",
      "epoch 81,train loss 0.011752,test loss 0.038455\n",
      "epoch 82,train loss 0.011752,test loss 0.038455\n",
      "epoch 83,train loss 0.011752,test loss 0.038455\n",
      "epoch 84,train loss 0.011752,test loss 0.038455\n",
      "epoch 85,train loss 0.011752,test loss 0.038455\n",
      "epoch 86,train loss 0.011751,test loss 0.038455\n",
      "epoch 87,train loss 0.011751,test loss 0.038454\n",
      "epoch 88,train loss 0.011751,test loss 0.038454\n",
      "epoch 89,train loss 0.011751,test loss 0.038454\n",
      "epoch 90,train loss 0.011751,test loss 0.038454\n",
      "epoch 91,train loss 0.011751,test loss 0.038454\n",
      "epoch 92,train loss 0.011750,test loss 0.038454\n",
      "epoch 93,train loss 0.011750,test loss 0.038454\n",
      "epoch 94,train loss 0.011750,test loss 0.038454\n",
      "epoch 95,train loss 0.011750,test loss 0.038454\n",
      "epoch 96,train loss 0.011750,test loss 0.038453\n",
      "epoch 97,train loss 0.011749,test loss 0.038453\n",
      "epoch 98,train loss 0.011749,test loss 0.038453\n",
      "epoch 99,train loss 0.011749,test loss 0.038453\n",
      "epoch 100,train loss 0.011749,test loss 0.038453\n",
      "epoch 101,train loss 0.011749,test loss 0.038453\n",
      "epoch 102,train loss 0.011749,test loss 0.038453\n",
      "epoch 103,train loss 0.011748,test loss 0.038453\n",
      "epoch 104,train loss 0.011748,test loss 0.038453\n",
      "epoch 105,train loss 0.011748,test loss 0.038453\n",
      "epoch 106,train loss 0.011748,test loss 0.038453\n",
      "epoch 107,train loss 0.011748,test loss 0.038453\n",
      "epoch 108,train loss 0.011747,test loss 0.038453\n",
      "epoch 109,train loss 0.011748,test loss 0.038452\n",
      "epoch 110,train loss 0.011747,test loss 0.038451\n",
      "epoch 111,train loss 0.011747,test loss 0.038451\n",
      "epoch 112,train loss 0.011747,test loss 0.038450\n",
      "epoch 113,train loss 0.011747,test loss 0.038450\n",
      "epoch 114,train loss 0.011746,test loss 0.038450\n",
      "epoch 115,train loss 0.011746,test loss 0.038449\n",
      "epoch 116,train loss 0.011748,test loss 0.038454\n",
      "epoch 117,train loss 0.011748,test loss 0.038455\n",
      "epoch 118,train loss 0.011748,test loss 0.038456\n",
      "epoch 119,train loss 0.011748,test loss 0.038457\n",
      "epoch 120,train loss 0.011747,test loss 0.038458\n",
      "epoch 121,train loss 0.011748,test loss 0.038460\n",
      "epoch 122,train loss 0.011748,test loss 0.038461\n",
      "epoch 123,train loss 0.011747,test loss 0.038462\n",
      "epoch 124,train loss 0.011747,test loss 0.038463\n",
      "epoch 125,train loss 0.011747,test loss 0.038463\n",
      "epoch 126,train loss 0.011746,test loss 0.038464\n",
      "epoch 127,train loss 0.011746,test loss 0.038464\n",
      "epoch 128,train loss 0.011746,test loss 0.038465\n",
      "epoch 129,train loss 0.011745,test loss 0.038465\n",
      "epoch 130,train loss 0.011745,test loss 0.038465\n",
      "epoch 131,train loss 0.011745,test loss 0.038466\n",
      "epoch 132,train loss 0.011745,test loss 0.038466\n",
      "epoch 133,train loss 0.011744,test loss 0.038467\n",
      "epoch 134,train loss 0.011744,test loss 0.038467\n",
      "epoch 135,train loss 0.011744,test loss 0.038467\n",
      "epoch 136,train loss 0.011744,test loss 0.038467\n",
      "epoch 137,train loss 0.011744,test loss 0.038468\n",
      "epoch 138,train loss 0.011743,test loss 0.038468\n",
      "epoch 139,train loss 0.011743,test loss 0.038468\n",
      "epoch 140,train loss 0.011743,test loss 0.038468\n",
      "epoch 141,train loss 0.011743,test loss 0.038468\n",
      "epoch 142,train loss 0.011743,test loss 0.038468\n",
      "epoch 143,train loss 0.011742,test loss 0.038468\n",
      "epoch 144,train loss 0.011742,test loss 0.038469\n",
      "epoch 145,train loss 0.011742,test loss 0.038469\n",
      "epoch 146,train loss 0.011742,test loss 0.038469\n",
      "epoch 147,train loss 0.011742,test loss 0.038469\n",
      "epoch 148,train loss 0.011742,test loss 0.038469\n",
      "epoch 149,train loss 0.011741,test loss 0.038469\n",
      "epoch 150,train loss 0.011741,test loss 0.038469\n",
      "epoch 151,train loss 0.011741,test loss 0.038469\n",
      "epoch 152,train loss 0.011741,test loss 0.038469\n",
      "epoch 153,train loss 0.011741,test loss 0.038469\n",
      "epoch 154,train loss 0.011741,test loss 0.038469\n",
      "epoch 155,train loss 0.011740,test loss 0.038469\n",
      "epoch 156,train loss 0.011740,test loss 0.038469\n",
      "epoch 157,train loss 0.011740,test loss 0.038469\n",
      "epoch 158,train loss 0.011740,test loss 0.038469\n",
      "epoch 159,train loss 0.011740,test loss 0.038469\n",
      "epoch 160,train loss 0.011740,test loss 0.038469\n",
      "epoch 161,train loss 0.011739,test loss 0.038469\n",
      "epoch 162,train loss 0.011739,test loss 0.038469\n",
      "epoch 163,train loss 0.011739,test loss 0.038469\n",
      "epoch 164,train loss 0.011739,test loss 0.038469\n",
      "epoch 165,train loss 0.011739,test loss 0.038469\n",
      "epoch 166,train loss 0.011739,test loss 0.038469\n",
      "epoch 167,train loss 0.011738,test loss 0.038469\n",
      "epoch 168,train loss 0.011738,test loss 0.038469\n",
      "epoch 169,train loss 0.011738,test loss 0.038469\n",
      "epoch 170,train loss 0.011738,test loss 0.038469\n",
      "epoch 171,train loss 0.011738,test loss 0.038469\n",
      "epoch 172,train loss 0.011738,test loss 0.038469\n",
      "epoch 173,train loss 0.011738,test loss 0.038469\n",
      "epoch 174,train loss 0.011737,test loss 0.038469\n",
      "epoch 175,train loss 0.011737,test loss 0.038469\n",
      "epoch 176,train loss 0.011737,test loss 0.038469\n",
      "epoch 177,train loss 0.011737,test loss 0.038469\n",
      "epoch 178,train loss 0.011737,test loss 0.038469\n",
      "epoch 179,train loss 0.011737,test loss 0.038469\n",
      "epoch 180,train loss 0.011737,test loss 0.038469\n",
      "epoch 181,train loss 0.011736,test loss 0.038469\n",
      "epoch 182,train loss 0.011736,test loss 0.038469\n",
      "epoch 183,train loss 0.011736,test loss 0.038469\n",
      "epoch 184,train loss 0.011736,test loss 0.038469\n",
      "epoch 185,train loss 0.011736,test loss 0.038469\n",
      "epoch 186,train loss 0.011736,test loss 0.038469\n",
      "epoch 187,train loss 0.011736,test loss 0.038469\n",
      "epoch 188,train loss 0.011736,test loss 0.038469\n",
      "epoch 189,train loss 0.011735,test loss 0.038469\n",
      "epoch 190,train loss 0.011735,test loss 0.038469\n",
      "epoch 191,train loss 0.011735,test loss 0.038469\n",
      "epoch 192,train loss 0.011735,test loss 0.038469\n",
      "epoch 193,train loss 0.011735,test loss 0.038469\n",
      "epoch 194,train loss 0.011735,test loss 0.038469\n",
      "epoch 195,train loss 0.011735,test loss 0.038469\n",
      "epoch 196,train loss 0.011735,test loss 0.038469\n",
      "epoch 197,train loss 0.011734,test loss 0.038469\n",
      "epoch 198,train loss 0.011734,test loss 0.038469\n",
      "epoch 199,train loss 0.011734,test loss 0.038469\n",
      "epoch 200,train loss 0.011734,test loss 0.038469\n"
     ]
    }
   ],
   "source": [
    "train_loss=[]\n",
    "test_loss=[]\n",
    "batch_size=5\n",
    "\n",
    "#模型训练\n",
    "for epoch in range(num_epochs):#外循环训练一轮\n",
    "    train_1,test_1=0.0,0.0\n",
    "    for X,y in data_iter(batch_size,train_feature,train_label):#内循环训练一个batch\n",
    "        y_hat=net(X) #计算模型输出\n",
    "        l=loss(y_hat,y).sum() #计算模型输出与真实数据之间的差距\n",
    "        \n",
    "        #梯度清零\n",
    "        if optimizer is not None:\n",
    "            optimizer.zero_grad()\n",
    "        elif params is not None and params[0].grad is not None:\n",
    "            for param in params:\n",
    "                param.grad.data.zero_()\n",
    "        #反向传播\n",
    "        l.backward()\n",
    "        optimizer.step()\n",
    "    train_1=loss(net(train_feature),train_label)\n",
    "    test_1=loss(net(test_feature),test_label)\n",
    "    train_loss.append(train_1.mean().item())\n",
    "    test_loss.append(test_1.mean().item())\n",
    "    print('epoch %d,train loss %f,test loss %f'%(epoch+1,train_1.mean().item(),test_1.mean().item()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fHL8RuA84DTgduC8ibqpIRWZmA0xEcPPNN9PW1kZbWxvt7e1cddVVnHzyyaxatYpTTz2Vm2++mdtuu+2gxi6m2NilrsnR28q+AmBEPEHu7bFmZoe9/OtxnHvuudxyyy1cdtllDBkyhNdff53a2lo6OzsZPnw4l19+OUOGDOGHP/xhl2XLOVV19tlnM3PmTFpaWogIFi5cyIIFC9i8efMBY+/atYvdu3czZcoUJk6cyMc+9rGKbHu3wSFpJwd+aA9yL1xHRHywIlWZmfVz+dfjmDx5Ml//+tf5zGc+A8CQIUP40Y9+RHt7OzfeeCNHHHEEtbW1zJ07F4BZs2YxefJk6uvre3xxfNy4ccycOZPx43MfWbv66qsZO3YsS5YsOWDsnTt3Fr0mR28r63ocA52vx2H2/uPrcfSuSlyPw8zMDEh4jcPMzHrfhAkT2Lt3b5e2BQsWcOqpp1apop45OMxswIoIct9QNHCtWLGi504VlvqShU9VmdmANHjwYLZv3578R8+6igi2b9/O4MGDy17GRxxmNiCNHj2ajo4OfL2dQzd48GBGjx5ddn8Hh5kNSLW1tTQ2Nla7jMOST1WZmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJalocEiaJGmdpHZJLUXmS9K92fyXJY3L2k+U9IyktZLWSLoub5nhkp6StD77OayS22BmZl1VLDgk1QBzgMnAKcDXJJ1S0G0yMCa7zQLmZu2dwD9ExCeBicC1ecu2AMsiYgywLJs2M7M+UskjjvFAe0RsiIh3gEeBqQV9pgIPRc5yYKik+ojYEhEvAkTETmAtMCpvmQez+w8CF1RwG8zMrEAlg2MUsClvuoO//PEvu4+kBmAssCJrOiEitgBkP48vtnJJsyS1Smr1xezNzHpPJYNDRdoipY+kIcATwPUR8ceUlUfEfRHRHBHNdXV1KYuamVk3KhkcHcCJedOjgc3l9pFUSy40Ho6In+T12SqpPutTD7zRy3WbmVk3KhkcLwBjJDVKOhK4FFhU0GcRMCN7d9VEYEdEbJEk4AfA2oi4q8gyV2T3rwCerNwmmJlZoUGVGjgiOiXNBpYANcD8iFgj6Zps/jxgMTAFaAd2A1dmi58JfAP4raS2rO2/R8Ri4HbgMUlXAf8BXFypbTAzswMpovBlh/ef5ubmaG1trXYZZmYDiqRVEdFc2O5PjpuZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklcXCYmVkSB4eZmSVxcJiZWRIHh5mZJXFwmJlZEgeHmZklqWhwSJokaZ2kdkktReZL0r3Z/JcljcubN1/SG5JWFyzzbUmvS2rLblMquQ1mZtZVxYJDUg0wB5gMnAJ8TdIpBd0mA2Oy2yxgbt68HwKTSgx/d0Q0ZbfFvVq4mZl1q5JHHOOB9ojYEBHvAI8CUwv6TAUeipzlwFBJ9QAR8RzwZgXrMzOzg1DJ4BgFbMqb7sjaUvsUMzs7tTVf0rBiHSTNktQqqXXbtm0pdZuZWTcqGRwq0hYH0afQXOAkoAnYAtxZrFNE3BcRzRHRXFdX18OQZmZWrkoGRwdwYt70aGDzQfTpIiK2RsS+iHgXuJ/cKTEzM+sjlQyOF4AxkholHQlcCiwq6LMImJG9u2oisCMitnQ36P7XQDLTgNWl+pqZWe8bVKmBI6JT0mxgCVADzI+INZKuyebPAxYDU4B2YDdw5f7lJT0C/A0wUlIH8K2I+AHwXUlN5E5pbQT+vlLbYGZmB1JETy8pDHzNzc3R2tpa7TLMzAYUSasiormw3Z8cNzOzJA4OMzNL4uAwM7MkDg4zM0vi4DAzsyQODjMzS+LgMDOzJA4OMzNL4uAwM7MkDg4zM0vi4DAzsyQODjMzS+LgMDOzJA4OMzNL4uAwM7MkDg4zM0tSsSsAvh+8+fY77NrT+d60VLpv/jzlTRQu0qVf3tzCsVViQgUjdh3v0Goo7FjO2AfOK6/WsurpjRq6e9DM7KA4OLpx91P/zoLlv6t2GVYhvR2MpTL4wH8Kiv/DcGDAlwj/cpfp5cwsNlyxYC7er+dexeotb6zy/kkpt/5iDngMy6jhUOsoY5eVNdb/mnYq4xuHF+l58Bwc3bhw3CiaThwK5C5wni//krtd5kX+3a5LRRTtRuHVe/OXK7VM4cxS4xVeGrhkvwOGLn5J4YOtNUrsl+6uXNxlH/fC2F0fp573XXfjlVtDYceu6yqv1kPdd72h2GjFVlH4nC/Wr9yxivUsus5uHrNulyuzjgPGK3usInWUvc6DG6tY4zFH1RTreUgcHN0Y++FhjP3wsGqXYWbWr/jFcTMzS+LgMDOzJA4OMzNL4uAwM7MkDg4zM0vi4DAzsyQODjMzS+LgMDOzJOrtT5j2R5K2AQf73SEjgT/0Yjm9pb/WBf23NteVpr/WBf23tvdbXR+JiLrCxsMiOA6FpNaIaK52HYX6a13Qf2tzXWn6a13Qf2s7XOryqSozM0vi4DAzsyQOjp7dV+0CSuivdUH/rc11pemvdUH/re2wqMuvcZiZWRIfcZiZWRIHh5mZJXFwdEPSJEnrJLVLaqliHSdKekbSWklrJF2XtX9b0uuS2rLblCrUtlHSb7P1t2ZtwyU9JWl99rNPr4Yl6eN5+6RN0h8lXV+t/SVpvqQ3JK3Oayu5jyTdnD3n1kk6t4/r+idJr0p6WdJCSUOz9gZJf8rbd/P6uK6Sj12V99e/5NW0UVJb1t6X+6vU34fKPcciwrciN6AGeA34KHAk8BJwSpVqqQfGZfePBf4dOAX4NnBDlffTRmBkQdt3gZbsfgvwj1V+HH8PfKRa+ws4GxgHrO5pH2WP60vAUUBj9hys6cO6vgwMyu7/Y15dDfn9qrC/ij521d5fBfPvBP5nFfZXqb8PFXuO+YijtPFAe0RsiIh3gEeBqdUoJCK2RMSL2f2dwFpgVDVqKdNU4MHs/oPABdUrhS8Ar0XEwX5zwCGLiOeANwuaS+2jqcCjEbE3Iv4v0E7uudgndUXE0ojozCaXA6Mrse7UurpR1f21nyQB04FHKrHu7nTz96FizzEHR2mjgE150x30gz/WkhqAscCKrGl2dlphfl+fEsoEsFTSKkmzsrYTImIL5J7UwPFVqGu/S+n6y1zt/bVfqX3Un553fwf8Im+6UdK/SfqlpLOqUE+xx66/7K+zgK0RsT6vrc/3V8Hfh4o9xxwcpalIW1XfuyxpCPAEcH1E/BGYC5wENAFbyB0q97UzI2IcMBm4VtLZVaihKElHAl8Bfpw19Yf91ZN+8byT9E2gE3g4a9oCfDgixgL/Ffjfkj7YhyWVeuz6xf4CvkbXf1D6fH8V+ftQsmuRtqR95uAorQM4MW96NLC5SrUgqZbck+LhiPgJQERsjYh9EfEucD8VOkTvTkRszn6+ASzMatgqqT6rux54o6/rykwGXoyIrVmNVd9feUrto6o/7yRdAZwPXBbZSfHstMb27P4qcufFT+6rmrp57PrD/hoEXAj8y/62vt5fxf4+UMHnmIOjtBeAMZIas/9cLwUWVaOQ7PzpD4C1EXFXXnt9XrdpwOrCZStc1zGSjt1/n9wLq6vJ7acrsm5XAE/2ZV15uvwXWO39VaDUPloEXCrpKEmNwBhgZV8VJWkScBPwlYjYnddeJ6kmu//RrK4NfVhXqceuqvsr80Xg1Yjo2N/Ql/ur1N8HKvkc64tX/QfqDZhC7h0KrwHfrGIdnyV3KPky0JbdpgALgN9m7YuA+j6u66Pk3p3xErBm/z4CRgDLgPXZz+FV2GcfALYDx+W1VWV/kQuvLcCfyf23d1V3+wj4ZvacWwdM7uO62smd/97/PJuX9b0oe4xfAl4E/raP6yr52FVzf2XtPwSuKejbl/ur1N+Hij3H/JUjZmaWxKeqzMwsiYPDzMySODjMzCyJg8PMzJI4OMzMLImDw6yfk/Q3kn5W7TrM9nNwmJlZEgeHWS+RdLmkldn1F/5ZUo2kXZLulPSipGWS6rK+TZKW6y/XvRiWtX9M0tOSXsqWOSkbfoikx5W7VsbD2aeFzarCwWHWCyR9EriE3Jc+NgH7gMuAY8h9X9Y44JfAt7JFHgJuiojTyH0ien/7w8CciDgd+E/kPqkMuW88vZ7ctRQ+CpxZ4U0yK2lQtQswe5/4AvBp4IXsYOBocl8q9y5/+fK7HwE/kXQcMDQifpm1Pwj8OPver1ERsRAgIvYAZOOtjOy7kLKrzDUAz1d8q8yKcHCY9Q4BD0bEzV0apVsK+nX3HT/dnX7am3d/H/7dtSryqSqz3rEM+Kqk4+G96z1/hNzv2FezPl8Hno+IHcD/y7u4zzeAX0buGgodki7IxjhK0gf6ciPMyuH/Wsx6QUS8Iul/kLsa4hHkvkH1WuBt4K8lrQJ2kHsdBHJfcz0vC4YNwJVZ+zeAf5Z0WzbGxX24GWZl8bfjmlWQpF0RMaTadZj1Jp+qMjOzJD7iMDOzJD7iMDOzJA4OMzNL4uAwM7MkDg4zM0vi4DAzsyT/HzI5CwpvmUnxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制loss曲线\n",
    "x=np.arange(num_epochs)\n",
    "plt.plot(x,train_loss,label=\"train_loss\",linewidth=1.5)\n",
    "plt.plot(x,test_loss,label=\"test_loss\",linewidth=1.5)\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制局部loss曲线\n",
    "x=np.arange(num_epochs)\n",
    "plt.plot(x,train_loss,label=\"train_loss\",linewidth=1.5)\n",
    "plt.plot(x,test_loss,label=\"test_loss\",linewidth=1.5)\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.legend()\n",
    "plt.xlim(5,num_epochs)\n",
    "plt.ylim(0,0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#预测函数，利用训练好的网络在测试集上进行测试、评估\n",
    "def predict(x):\n",
    "    temp=torch.from_numpy(x)\n",
    "    x_tensor=temp.reshape(1,1,window_size-1)\n",
    "    return net(x_tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_predict=[]\n",
    "split_point=int(split_prop*int(series.size))\n",
    "for i in range((split_point-(window_size-1)),(series.size-window_size+1)):\n",
    "    x=series[i:i+window_size-1]\n",
    "    y=predict(x)\n",
    "    test_predict.append(y)\n",
    "test_time=time[split_point:]\n",
    "plt.figure(figsize=(10,6))\n",
    "plot_series(test_time,test)\n",
    "plot_series(test_time,test_predict)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
